Q) Define Research and Explain the nature and importance of Research.Research in common parlance refers to a search for knowledge. One can also define research as a scientific and systematic research for pertinent information on a specific topic. In fact,' research is an art of scientific investigation. '

Research is a careful investigation or inquiry especially through search for new facts in any branch of knowledge.

According to Redman and Mory, "Research is a systematized effort to gain new knowledge".

According to Fred Kerlinger, "Research is an organized enquiry designed and carried out to provide information for solving a problem".

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According to Francis Rummel, "Research is a careful inquiry or examination to discover new information or relationships and to expand and to verify existing knowledge".

According to Robert Ross, "Research is essentially an investigation, a recording and analysis of evidence for the purpose of gaining knowledge".

Research can be defined as logical and systematized application of the fundamentals of science to the general and overall questions of a study, and scientific techniques which provide precise tools, specific procedures and technical, ,rather than philosophical means for getting and ordering the data prior to their logical and manipulation. "

Research represents a systematic method of exploring actual persons and groups, focused primarily on their experience within their social worlds, inclusive of social attitudes and values, the mode of analysis of these experiences which permit stating proposition in the form.

In short, the search for knowledge through objective and systematic method of finding solution to a problem is research.

i) Nature of Research1) Research is a systematic and critical investigation into a phenomenon.2) It is not a mere compilation, but a purposive investigation; it aims’ at describing, interpreting and explainingphenomenon.3) It adopts scientific method.4) It is objective and logical, applying possible tests to validate the measuring tools and the conclusions reached.5) It is based upon observable experience or empirical evidence.6) Research is directed towards finding answers to pertinent questions and solutions to problems.It emphasizes the development of generalization, principles or theories.8) The purpose of research is not to arrive at an answer, which is personally pleasing to the researcher, but Rather one, which will stand up the test of criticism.9)I t i s trans-disciplinary in nature

ii) Objectives of Research1) Research Extends Knowledge: Research extends k n o w l e d g e o f human beings, social life a n d environment. Scientists and researchers build up the wealth of knowledge through their research findings. They search answers for various types of questions: What, Where, When, How and Why of various phenomena, and enlighten us. The bodies of knowledge have been developed by research in general and pure or fundamental research in particular.

2) Research Unravels the Mysteries o f Nature: It brings to light hidden information that might never be discovered fully during the ordinary course of life.

3) Research Establishes Generalizations and General Laws: Research establishes generalizations and general laws and contributes to theory building in various fields of knowledge. The knowledge of isolated events is connected together to draw generalizations a n d general laws. Law of gravitation, Law of demand, and principles of

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organization such as unity of command and scalar principle, the theory of consumer behavior and motivation theories are some examples for such generalizations, laws and theories.

4) Research Verifies and Tests: Research verifies and tests existing facts and theory and these help improving knowledge and ability to handle situations and events. Merton argues: "Empirical research goes far beyond the passive role of verifying and testing theory. Research plays an active role, it performs at least four major functions-initiates, formulates, deflects, and clarifies theory."5) General Laws Developed 'through Research: General laws developed through research may enable us to make reliable predictions of events yet to happen.

6) Research Analyze Inter-relationships: Research aims to analyze inter-relationships between variables and to derive causal explanations and thus enables to have a better understanding of the world in which we live.

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7) Applied Research Aims at Finding Solutions: Applied research aims at finding solutions to problems socio-economic problems (e.g., social unrest, unemployment, poverty) health problems, human relations problems in organizations and so on. Thanks to the fruits of research, having better quality of life, longer life span and better control over events.

8) It Aims to Develop Tools, Concepts: Research also aims at developing new tools, concepts, and theories for a better study of unknown phenomena.

9 ) Research Aids in Planning: Research aids planning and thus contributes to national development. Research-social science research in particular - aids planning in the following ways:

i) Research brings out factual data on prevailing situations and problems for drawing up plans and schemes on a realistic basis. Research uncovers needed facts on which sound decisions can be made, before committing resources. Studies open up the possibility of testing the validity of planning assumptions or premises.

ii) Research studies enable the planners to evaluate alternative strategies and choose the most appropriate strategies for development of the various sectors like agriculture, industry, education, health, social welfare etc.

iii) The dissemination of research finding creates a general awareness of the country’s current situations and problems among the public, which inspire them to participate in formulation and implementation of development schemes.

10) Rational Decis ion Making: Analytical studies of internal and external environment of business and non business organizations provide factual data for rational decision making--formulation of strategies and policies. Studies of their operational problems contribute to an improvement in their performance.

Q) Explain the various Types of ResearchThe basic types of research are as follows:1) Descriptive vs. Analytical: Descriptive research includes surveys and fact-finding enquires ofDifferent kinds. The major purpose of descriptive research is description of the state of affairs, as it exists at present. In social science and business research we quite often use the term Ex post facto research for descriptive research studies. The methods of research utilized in descriptive research are survey methods of all kinds, including comparative and correlation methods. In analytical research, on the other hand, the researcher has to use facts or information already available, and analyze these to make a critical evaluation of the material.

2) Applied Vs. Fundamental: Research can either be applied (or action) research or fundamental (or basic or pure) research. Applied research aims at finding a solution for an immediate problem facing a society or an industrial/business organization, where as fundamental research is mainly concerned with generalizations and with the formulation of the theory.3) Exploratory Research: When the purpose of research is to gain familiarity with a phenomenon or acquire new insights into it in order to formulate a more precise problem or develop hypothesis, the exploratory studies come in handy. If the theory happens to be too general or too specific, a hypothesis cannot be formulated. Therefore a need for an exploratory research is felt to gain experience that will be helpful in formulating relevant hypothesis for more definite investigation.

For example, a researcher in the field of Psychology is interested in studying the influence of social environment on mental health. The researcher is restrained from formulating any precise hypothesis for investigation based on the writings on this topic. In such a case the exploratory study is usually most suitable.

The following are the three approaches to the exploratory study:i) Survey of Literature: A review of the literature helps to identify the hypothesis which may serve as a guide for

further investigation.ii) Experience Survey: A small portion of existing knowledge and experience is put into written form.

\ IEveryday experience provides opportunity to obtain information required to formulate hypothesis.iii) Case Study: The focus may be on individuals or situations or groups or communities. The method of study may lay stress on the examination of the existing records. It may be unstructured interviewing or participant observation or some other approach. -1 It is important to bear in mind that exploratory study merely leads to insights for formulating hypothesis. Its approaches do not consider it important to test or demonstrate them.

4) Historical Research: Historical research is the research on past social forces which have shaped the present. For example, to study the present state of Indian labor we may research on past historical forces.

5) Experimental Research: Although experimental research is primarily possible in areas of physical sciences, with the help of hypothesis, may also be carried out in social sciences if such research enables us to quantify the findings, to apply the statistical and mathematical tools and to measure the results thus quantified. It is also classified under conclusive research. '

6) Ex-Post-Facto Research: Ex-post-facto research is an empirical enquiry for situations that have already occurred. For example, market failure for any companies' product if studied or researched later may be categorized as ex-post-facto research. Apart from this, declaration or slow rate of growth in national income when studied to reformulate the future policies on this account is classified as ex-post-facto Research.

7) Quantitative vs. Qualitative: Quantitative research is based on the measurement of quantity or amount. It is applicable to phenomena that can be expressed in terms of quantity. Qualitative research, on the other hand, is concerned with qualitative phenomenon, i.e., phenomena relating to or involving quality· or kind. For example, when we are interested in investigating the reasons for human behavior (i.e., why. people think or do certain things), we quite often talk of 'Motivation Research', an important type of qualitative research. Other techniques of such research are word association tests, sentence completion tests, story completion tests and similar other projective techniques.

8) Conceptual vs. Empirical: Conceptual research is that related to some abstract idea(s) or theory. It is generally used by philosophers and thinkers to develop new concepts or to reinterpret existing ones. On the other hand, empirical research relies on experience or observation alone, often without due regard for system and theory. It is data-based research, coming up with conclusions which are capable of being verified by observation or experiment. We can also call it as experimental type of research.

9) Some other Types of Research: All other types of research are variations of one or more of the above stated approaches, based on either the purpose of research, or the time required to accomplish research, or the environment in which research is done, or on the basis of some other similar factor. From the point of view of-time, we can think of research either as one-time research or longitudinal research. In the former case the research is confined to a single time-period, whereas in the latter case the research is carried on over several time-periods. Research can be field-setting research or laboratory research or simulation research, depending upon the environment in which it is to be carried out. Research can as well be understood as clinical or .diagnostic research. Such research follows case-study methods or in-depth approaches to reach the basic casual relations. The research may be exploratory or it may be formalized.The objective of exploratory research is the development of hypotheses rather than their testing, whereas formalized research studies are those with substantial structure and with specific hypotheses to be tested. Research can also be classified as conclusion-oriented and decision-oriented. While doing conclusion oriented research, a researcher is free to pick up a problem, redesign the enquiry as he proceeds and is prepared to conceptualize as he wishes. Decision-oriented research is always for the need of a decision maker and the researcher in this case is not free to embark upon research according to his own inclination.

Q) Explain the RESEARCH PROCESS Research process consists of a number of closely related activities. But such activities overlap continuously and do not follow a strictly prescribed sequence. Various steps involved in a research process are not mutually exclusive; nor are they separate and distinct. They do not necessarily follow each other in any specific order and the researcher has to be constantly anticipating at each step in the research process the requirements of the subsequent steps. However, the following order concerning various steps provides a useful procedural guideline regarding the research process:1) Defining research problem2) Extensive literature survey3) Formulation of hypotheses4) Preparing the research design5) Determining sample design6) Collecting the data7) Execution of the project8) Analysis of data9) Testing of hypothesis10) Generalizations and interpretation and11) Preparation of the report or presentation of the results, i.e., formal write-up of conclusions reached.

1.2.1: Defining Research ProblemThe first step in research is formulating a research problem. It is most important stage in applied research, as poorly defined problems will not yield useful results. It is rightly said that, "A problem well defined is half-solved". Poorly defined problems cause confusion and do not allow the researcher to develop a good research design.

After a problem has been chosen, the next task is to formulate it precisely. This is too needs a good deal of care on the part of marketing researchers.

Essentially two steps are involved in formulating the research problem, viz., understanding the problem thoroughly, and rephrasing the same into meaningful terms from an analytical point of view.

The researcher must examine all available literature to get himself acquainted with the selected problem. He may review two types of literature- the conceptual literature concerning the concepts and theories, and the empirical literature consisting of studies made earlier, which are similar to the one proposed.

The basic outcome of this review will be the knowledge as to what data and other materials are available for operational purposes, which will enable the researcher to specify his own research problem in a meaningful context. After this the researcher rephrases the problem into analytical or operational terms, i.e., to put the problem in as specific terms as possible.

1.2.1.1. Steps in Problem Definition

In designing any research problem the researcher should have the following information:1) The nature of decision-maker, the environment in which he operates and the resources at his disposal.2) The quantification of research objectives in measurable terms.3) The alternative strategies possible for the solution of the problem.4) Evaluation of various alternative strategies. . The following is the process of problem formulation: 1) Systematic immersion in the subject matter through first hand observation i.e. pilot .survey, preliminary investigation etc.2) Study of relevant literature on the subject.3) Discussion with persons having rich practical experience in the field study.

Problem formulation requires thorough knowledge of the phenomenon as well as experience in the line It requires considerable consultations to know the ins and outs of the business and other related factor. Problem formulation basically consists of three steps:1) Identification of the Problem: Identification of problems in marketing research is most important phenomenon. In general, a problem exists whenever one faces a question whose answer involves some doubt or uncertainty. The existence of the problem can be identified on the basis of following characteristics:

i) Presence of Some Symptomatic Situation: To sense a problem one should develop an aptitude of understanding different types of difficulties or symptoms. Symptomatic situations can be classified as:

a) Overt Difficulties: These are situations generally experienced in, routine working For example; lagging sales volume is a symptom.

b) Latent Difficulties: These are difficulties that are not yet evident but are likely to aggravate and become overt For example, due to lagged sales volume the moral of the sales force will also decline. But this will be evident only after some time say 6 to 12 months. Thus a symptom is a condition that indicates the existence of a problem. Decision-maker can be aware of these symptoms through: ,•• Information channels: These can be trade news or other literary sources.• Formal research studies in other fields.

•Performance analysis viz., sales market share, distribution, cost and profit studies within the organization.

ii) There should be More than One Solution to the Problem with Some Uncertainty Associated with it. If there is no solution or answer to some difficulty then it is not a problem. Similarly, a problem exists only if there are at least two or more alternatives or actions that could be taken to solve it and there is always some doubt as to which alternative is best.

2) To Locate Probable Alternatives: Researcher should enlist all possible causes responsible for the occurrence of the problem and arrange them in order of their probable importance. Then there should be a discussion with the decision-maker regarding each of the alternatives and its implications and asking him whether he follows that particular course of action. Where he says 'no' further probing will usually reveal objectives hich are not served by the course of action. This can also help in finding the degree of uncertainty associated with each alternative strategy. The researcher would investigate each alternative, eventually electing the most appropriate one. Gathering information to accept or reject these various statements accomplishes the study's objectives. The probing of various courses of actions associated with solution of a problem helps in:i) Setting up the hypothesis which is likely to support further research.ii) Assessing the nature and magnitude of the problem.

iii) Providing familiarity with environment and realistic projection of situation changes.

iv)Correct estimation of risk associated with particular solution.

Some problem solving research may also be fairly precise, so establishing formal hypothesis would add little to the clarity of their findings. On the other hand, most basic research projects should include working hypothesis to give greater credence to their findings.

3)Appropriate Marketing Information System: The essential purpose of marketing research is to provide relevant information which facilitates the identification of an opportunity or problem situation. The mark of the brilliant manager is the capacity to filter the information flows and identify the areas that may impede the achievement of organization's objectives. Relevant and reliable information is likely to reduce the degree of uncertainty with respect to the consequences of some major decisions.

At this stage a list of the precise types of information needed to accomplish the study's objectives and test its hypothesis should be determined. Infact, the activity of identifying the information needed begins in the funneling process and continues throughout all the early stages of the investigation.But the identification of the specific information needed to evaluate various alternative courses of action can be generated by appropriate marketing information system only.

1.2.1.2. Components of Problem Formulation Process

It is evident that problem formulation is very important for planning and implementing research (investigations. Though the nature of formulation process will mostly depend on the type of problem, objectives of the organization, aptitude of the decision-maker and the researcher but some common components observed in general are given in figure Necessary modifications and adjustments can be done according to the situation.

1) Decision-Maker Policies: Researcher should make every effort to learn about the goals and attitude of the individual responsible to take the final decision and for whom the information is to be collected.

For this knowledge of the environment with in which the decision-maker operates is important.

It informs about the resources to be tapped and the realistic course of action.

2) Objectives of the Decision-Maker: In spelling out the objectives of the investigation the researcher must explore the answer of the question."What is the purpose of this study?"

3) Determining Alternative Courses Of Actions: Exploratory research is one way to learn more about a problem or opportunities as well as in sorting and identifying alternative courses of actions.

4) Evaluation of the Consequences of Various Alternatives: Formalizing a decision process is vital for understanding a problem. It should benefit both researcher and the decision-maker. Conclusive research can be used in the evaluation of the various alternatives determined in step (3).

5) Preparation of the list of information needed

6) To anticipate the possible findings of the research project.

Advantages of Problem Formulation:

It is experienced that sometimes a vaguely formulated problem introduces many difficulties in proper decision

making as well as to conduct true and relevant research. A proper definition not only arrives at an operational statement but it also uncovers the basic problem that underlines the symptoms which' are to be solved. The following are-the main advantages of problem formulation:

1) It orients, i.e., brings into clear understanding of the relations and determines the position of decision-maker and the researcher within the framework of classified marketing.

2) It tries to relate the problem with other marketing problems by finding hidden difficulties and new opportunities.

3) Suggests the source of data and facilitates their interpretation.

4) Determines the action needing priority and the one which needs more detailed investigation.

5) Enables the decision model to be well conceived.

6) Identifies the data relevant to the problem.

7) Pinpoints the gaps in the knowledge that may call for formal research.

Extensive Literature Survey:

Once the problem is formulated, the next step is to write down a brief summary. For this the researcher should undertake extensive literature survey connected with the problem. For this purpose, the abstracting and indexing journals and published or unpublished bibliographies are the first place to go to. Academic journals, conference proceedings, government reports, books etc., must be taped depending on the nature of the problem.

Purposes of Review:The reasons for review of related literature are:

1) To gain a background knowledge of the researchtopic,

2) To identify the concepts relating to it, potential relationships between them and to formulate research able hypothesis,

3) To identify appropriate methodology, research design, methods, of measuring concepts and techniques of analysis,

4) To identify data sources used by other researchers, and

S) To learn.how others structured their reports.

The kinds of literature to be reviewed at the various stages of the research processes and the specific purposes of the review are indicated below.

Literature Search Procedure:

The above table shows that a researcher has to review the various kinds of literature relating to the selected field study. How can he identify the related materials.This research procedure involves a series of steps. The exact sequence will vary depending upon the subject and the knowledge of the researcher.A general approach suggested below:

1) Request learned professors, librarians or others familiar with the field to suggest relevant references.

2) Find. out whether any bibliography already prepared on the subject is available in the library. See the

Bibliographic index, if any, maintained in the library.

3) Consult bibliographies in the theses on the topic and related topics.

See the card catalogues of the library: i) Author catalogue cards if the authors of books are known,

(ii) Subject catalogue cards to locate the titles and other details of the books on the subject.

5)Examine periodicals, monographs, reports and conference proceedings and other materials including microfilms available in the library.

6) Consult reference cited in the books and articles already located. Each book or article will be a means for locating additional references.

7) Consult the abstract Journal on the subject or 'Abstracts' section in the journals relating to the subject. See the 'Book-Review' pages in the daily newspapers and in the journals.

Thus one can identify many references relating to the selected topic. The problem now is to go through the references one after another and extract information relevant to the study.

Sources of Literature:

The sources of documentary information, which can aid the process of locating literatures relating to selected

research topics, are:

1) Subject Catalogues of Libraries: These catalogues furnish lists of books available on various subjects.

Subject Index in libraries also serves the same purpose.

2) Documentation Services: There are a number of documentation centres attached to national institutions.

Some of the-important centres are:

i) Social Sciences Documentation Centre of ICSSR.

ii) National Documentation Centre of Mass Communication, New Delhi. iii) Small Enterprises National Documentation Centre, Hyderabad.

iv) Centre for Rural Documentation, Hyderabad.

v) National Council of Applied Economic Research, New Delhi. vi) Centre for Economic and Social Studies, Hyderabad.

From these centres codified information on any topic can be obtained on payment of a nominal fee. In addition, Xerox copies of pages in books or journals can also be obtained from these centres.

3) Bibliographies: Some institutes and libraries bring out bibliographies of books and papers published in

India. Important bibliographies are:

i)Indian National Bibliography: This is a monthly publication of National Library, Calcutta to which copies of all books published should be delivered under the Delivery of Book Act. This publication contains a latest list of books published in all the 15 major languages of India. A five-year cumulative index is also available

ii)The library Congress Accession list ,South Asia: This is a monthly record of all publications acquired by the US Library Congress Office in New Delhi from Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka

iii) Asian Social Science Bibliograpby : This is an annual publication of the Institute of Economic Growth, New Delhi.

It ‘covers selective books, reports and papers published in English in Asia.

iv) Bibliographies of Libraries: The libraries of some Universities and other educational institutions bring

out bibliographies on selected subjects.

4) Lists of Books and Publishers' Bulletins: \

i) All leading publishers bring out periodical bulletins and list of books published and forthcoming books,

Some publishers publish bulletins periodically, for example, "Publishers Monthly" (C. S. Chand and Co.), "The Book Maker" (Orient Longman), "Book Selection" (Allied Publishers), "Recent Indian Books" (Federation of Publishers and Booksellers' Association in India), etc.

ii) Book Review Columns of Journals contain a short review of the latest books; Newspapers also give a list of latest publications in their weekly book review columns.

iii) Cumulative Book Index: World List of Books in the English Language' Published since 1928 by H.W.

Wilson, New York.

Journals: The names of journals and index of articles published in them are available from various sources.

They are:

i) Index India: This is a quarterly documentation list published by the Rajasthan University Library. It

consists of Newspaper Index, Index to Indian Periodicals, Index to Foreign Periodicals, Index to

bibliographical Profiles, Index to Book Reviews, and Index to Theses and Documents.ii) Guide to Indian Periodical Literature: This is published as a quarterly by the Indian Documentation

Centre, Gurgaon. It covers about 300 periodicals.

iii) Indian Press index: This is an index of all articles, special write-ups, editorials and letters published in 25 daily English newspapers in India.

iv)Documentation Fortnightly: This is brought out by the Parliament Library with a view to keeping the members of Indian Parliament well informed of current materials contained in various documents received by the Parliament Library during the fortnight.

v) Documentation of Asia: It is an annual classified bibliography of articles on Asia, published by the Indian Council of World Affairs.

vi) Indian Index Series: The Social Sciences Documentation Centre of ICSSR is bringing out' Indexes of articles on various subjects published in various joumals so far.

6) Government Reports: Government publishes administrative reports of various departments, reports of

Commissions and Committees, "India - A Reference Annual" etc.

i)Catalogue of Government of India Civil Publications (Subject-wise analyzed, 1969).

ii) Catalogue of Government 'of India Publications, 1980.

iii)Government of India Publications (by Mohinder Singh), 1982.

iv) Parliament Library Bulletin (contains a separate section of government publications).

v) Statistical Abstracts – India

7)Research Abstracts: Abstracts of researches completed are available from the following publications:

i) ICSSR Research Abstracts: Contain abstracts of research projects funded by ICSSR. .L

ii) Indian Dissertation Abstracts: Publislied by ICSSR, gives synopsis of Ph.D. theses in Social Sciences submitted to Indian Universities.

iii) ICSSR Journal of Abstracts and Review Economics: Contains abstract of selected articles and reviews of books published in Indian Economic Periodicals.

iv) ICSSR Journal of Abstracts and Review: Political Science.

v) ICSSR Journal of Abstracts and Reviews: Geography.

vi) Dissertation Abstracts International: 1938 to date published by Xerox University, Ann Arbor, Michigan.

8) Informatlon on Research Done: Information on Doctoral research work already done is available from the following sources:

i)Bibliography of Doctoral Dissertations Accepted By Indian Universities (social sciences and humanities): Published by the Association of Indian Universities: First volume covers the period of 1957-70, second 1970-75. Thereafter, it is published as an annual publication.

ii)Doctorates in Social Sciences Awarded By Indian Universities: Published by ICSSR, New Delhi in 5 volumes; 1957-67, 1968, 1869, 1970 and 1971.

iii)University News: A weekly publication of Association of Indian Universities contains a section on dissertations accepted by Indian Universities.

iv)ICSSR Survey of Research in Social Sciences: First Survey completed in 1970-71; published in 22 volumes.

v)Foreign Theses on India: A publication of Social Sciences Documentation Centre of ICSSR.

vi)American Doctoral Dissertations: Published since 1957 by Xerox University Microfilms, Anna Arbor, Michigan, provides list of all doctoral dissertations accepted by American and Canadian Universities.

Formulation of Hypotheses:

Now the researcher should state in clear terms the working hypothesis or hypothesis. Working hypothesis is tentative assumption made in order to draw out and test its logical or empirical consequences. As such the manner in which research hypothesis are developed is particularly important since they provide the focal point research. Hypothesis should be very specific and limited to the piece of research in hand because it has to be tested The role of the

hypothesis is to guide the researcher by delimiting the area of research and to keep him me right track.

Working hypothesis can be developed by using the following approach:

1)Discussion with colleagues and experts about the problem its origin and the objectives in seeking a solution, 2)Examination of data and records, if available, concerning the problem for possible trends, peculiarities and other clues,

3)Review of similar studies in the area or of the studies on similar problems, and

4)Exploratory personal investigation, .which involves original field interviews on a limited scale with interested parties and individuals with a view to secure insight into the practical aspects of the problem.

Working hypothesis are more useful when stated in precise and clearly defined terms.

A basic fact about testing hypothesis is that a hypothesis may be rejected but that the hypothesis never can be conditionally accepted until all possible evidence is evaluated. In the case of sampled data, the information set cannot be complete. So, if a test using such data does not reject a hypothesis, the conclusion is not neceessarily that the hypothesis should be accepted .

The null hypothesis in an experiment is the hypothesis that the independent variable has no effect on the Independent variable. The null hypothesis is expressed as H0.This hypothesis is assumed to be true unless proven otherwise The alternative to the null hypothesis is the hypothesis that the independent variable does have an effect on the dependent variable. This hypothesis is known as the alternative, research or experimental hypothesis and is expressed as HI. This alternative hypothesis states that the relationship observed between the variables cannot be explained by chance alone.

There are two types of errors in evaluating hypothesis:

1)Type I Error: It occurs when one rejects the null hypothesis and accepts the alternative, when in fact the null hypothesis is true.

2)Type II Error: It occurs when one accepts the null hypothesis when in fact the null hypothesis is false.

Steps in Hypothesis Testing:

1)Formulate a Hypothesis: The conventional approach to hypothesis testing is to set up two hypotheses instead of one in such a way that if one hypothesis is true, the other is false. Alternatively, if one hypothesis is false or rejected, then the other is true or accepted. These two hypothesis are:

i) Null hypothesis, and

ii) Alternative hypothesis.

The term "null" means nothing or invalid. Assume that the mean of the population is and the mean of 'the sample is x. Since it has been assumed that the population has a mean of, this is our null hypothesis. We may write it as Where H0, is 'the null hypothesis. The alternative hypothesis is as

H0:µ=µ0

The rejection of the null hypothesis will show that the mean of the population is not .This implies that some other hypothesis is accepted. This other hypothesis is called the alternative hypothesis. It may be noted that there can be two or more alternative hypothesis though only one alternative hypothesis can be tested at one time against the null hypothesis.

2) Set-up a Suitable Significance Level: Having formulated the hypothesis, the next step is to test its validity at a certain level of significance. The confidence with which a null hypothesis is rejected or accepted depends upon the significance level used for the purpose, a significant level of, say 5 per cent, means that in the long run, the risk of making the wrong decisions are about five percent. The researcher is likely to be wrong in accepting a false hypothesis or in rejecting a true hypothesis in 5 out of 100 occasions.

3)Select Test Criterion: The next step in hypothesis testing is the selection of an appropriate statistical technique as a test criterion.There are many techniques from which one is to be chosen.

For example, when the hypothesis pertains to a large sample (30 or more), the Z-test implying normal distribution is used. When a sample is small (less than 30), the use of the Z-test will be inappropriate. Instead, the t-test will be more suitable. The test criteria which are frequently used in hypothesis testing are Z, t,F and X2.

4) Compute:After having selected the statistical technique to verify the hypothesis, the next step is the performance of various computations, necessary for the application of that particular test.These computations include the testing statistic as also its standard error.

5) Make Decisions: The last step in hypothesis testing is to draw a statistical decision, involving the acceptance or rejection of the null hypothesis. This will depend on whether the computed value of the test criterion falls in the region of acceptance or in the region of rejection at a given level of significance. It may be noted that the statement rejecting the hypothesis is much stronger than the statement accepting the hypothesis.

Features of a Good Hypothesis:

A hypothesis is a logical supposition, a reasonable guess, an educated conjecture or a proposed answer to the posed research problem(s) or observed phenomenon or phenomena to be researched and which may give direction to thinking and therefore aid in solving it. Hypotheses indicate where to search for data and how to interrelate this information. The solution of a research problem is commenced by collecting data after stating the hypothesis. Data, as such, does not present a solution to a problem, but merely confronts the researcher who has a hypothesis to test. The data and the interrelationships between the data, representing a coherent description or explanation of situations or events that have led to the problem, are specified by the hypothesis.

A hypothesis is important to the researcher because it sets an end goal to which his or her research can be directed in order to reveal relevant data. Once again, it is important to realize that hypothesis need not necessarily be confirmed. A hypothesis can also be rejected without prejudicing the value and acceptability of the research. A hypothesis is merely a forecast that has to be tested objectively by means of scientific methods.

NB: A hypothesis must always be formulated in such a way that it can be tested.

A hypothesis is testable when it can be proved true or untrue. Both alternatives must be possible. If one deliberately trying to prove the hypothesis, it will Jeopardize the impartiality of the research. A hypothesis has, in fact, nothing to do with proof, but its acceptance or rejection depends rather on what has been revealed by the facts.

T h e f o l l o w i n g r e q u i r e m e n t s c a n b e s e t f o r a c o r r e c t l y f o r m u l a t e d h y p o t h e s i s :

1) It must be stated clearly and precisely.2) It must be testable3) It must establish relationships between variables4) It must have a limited scope5) It must bear relation to aiready known facts6) As far as possible it must be stated in sample terms7) It must be possible to test it within a reasonable period

Research design is the conceptual structure within which research should be conducted. A research design

Specifies the methods and procedures for conducting a particular study. The researcher should specify the approach he intends to use with respect to the proposed study. The function of research design is to provide for the collection of relevant evidence with minimal expenditure of effort, time and money. Research designs can be grouped into three categories - exploratory research, descriptive research and causal research.

1)Exploratory Research: An exploratory research focuses on the discovery of ideas and is generally based

on secondary data. It is preliminary investigation, which does not have a rigid design.

2)Descriptive Research: A descriptive study is undertaken when the researcher wants to know the characteristics of certain groups such as age, sex, educational level, income, occupation, etc. In contrast to exploratory studies, descriptive studies are well structured.

3)Causal Research: A causal research is undertaken when the researcher is interested in knowing the cause and effect relationship between two or more variables. Such studies are based on reasoning along well- tested lines.

Determining Sample Design

All the items under consideration in any field of inquiry constitute a 'universe' or 'population'. A complete enumeration of all the items in the 'population' is known as a census inquiry. In such an inquiry when all the Items are covered no element of chance is left and highest accuracy is obtained. But in practice this may not be true. This type of inquiry involves a great deal of time, money and energy, not only this, census inquiry is not possible in practice under many circumstances.

The researcher must decide the way of selecting a "sample" or the sample design. A sample design is a definite plan determined before any data are actually collected for obtaining a sample from a given population. Samples can be either probability samples or non-probability samples. With probability samples each element has a known probability of being included in the sample but the non-probability samples do not allow the researcher to determine this probability.

Important sample designs are as follows:

1)Deliberate Sampling:Also known as purposive or non-probability sampling, this sampling method involves purposive or deliberate selection of particular unit of the universe for constituting a sample which represents the universe. When population elements are selected for inclusion in the sampling based on the ease of access, it can be called convenience sampling.

In judgment sampling the researcher's judgment is used for selecting items, which he considers as representative of the population. Judgment sampling is used quite frequently in qualitative research where the desire happens to be to develop hypothesis rather than to generalize to larger populations. .

2) Simple Random Sampling:This type of sampling is also known as chance sampling or probability sampling where each and every item in the population has an equal chance of inclusion in the sample and each one of the possible samples, in case of finite universe, has the same probability of being selected. In case of infinite population, the selection of each item in a random sample is controlled by the same probability and that successive selections are independent of one another.

3)Systematic Sampling.:Where an element of randomness is introduced by using random numbers to pick up the unit with which to start, this process of sampling is known as systematic sampling

, ..

This procedure is useful when sampling frame is available in the form of a list. In such a design the selection process starts by picking some random point in the list and then every nth element is selected until the desired number is secured.

4)Stratified Sampling: If the population from which a sample is to be drawn does not constitute a homogeneous group, then stratified sampling technique is applied so as to obtain a representative sample. In this technique, the population is stratified into a number of non-overlapping subpopulations or strata and sample items are selected from each stratum. If the items selected form each stratum is based on simple random sampling the entire procedure, first stratification and the simple random sampling, is known as stratified random sampling.

5)Quota Sampling: In stratified sampling the cost of taking random samples from individual strata is often so expensive that interviewers are simply given quota to be filled from different strata, the actual selection of items for sample being left to the interviewer's judgment. This is called quota sampling. The size. of the quota for each stratum is generally propionate to the size of that stratum in the population. Quota sampling is thus an important form of non-probability sampling. Quota samples generally happen to be judgment samples rather than random sample.

6) Cluster Sampling and Area Sampling: Cluster sampling involves grouping the population arid' then selecting the groups or the clusters rather than individual elements for inclusion in the sample. The clustering approach can, however, make the sampling procedure relatively easier and increase the efficiency of fieldwork, especially in the case of personal interviews.

Area sampling is generally done when the total geographical area of interest is big one. Firstly the total.area is divided into a number of smaller non over lapping areas, generally called geographical clusters, then a number of these smaller areas are randomly selected and all units in the small areas are included in the sample.,Area sampling is especially helpful where it do not have the list of the' population 'concerned. It also makes the field interviewing more efficient since interviewer can do many interviews at each location.

7) Multi-Stage Sampling: This is a further development of cluster sampling, This technique is meant for big inquiries extending to a considerably large .geographical area like an.entire country. The first stage is to select large primary sampling units such as states, then districts, .then towns and finally certain families within towns

If the techniques of random-sampling are applied at all stages, the sampling procedure is described as multistage random sampling. .

8)Sequential Sampling:This is somewhat· complex sample design where the ultimate size of the sample is not fixed in advance but is determined according to mathematical decisions on the basis of information yielded as survey progresses. This design is usually adopted under acceptance sampling plan 'in the context of statistic quality control.

In practice, several methods of sampling may be used in the same study, and then it can be called mixed sampling.''

Collecting the Data:

The next step is to determine the sources of data to be used. The researcher has to decide whether he has to collect primary data or depend exclusively on secondary data. Sometimes, the research study is based on both secondary and primary data.

The primary data are those, which are collected afresh and for the first time, and thus happen to be original in character.

The secondary data, on the other hand, are those which have already been collected by someone else and which have already been passed through the statistical process.

Any statistical data can be classified under two categories depending upon the sources utilized. These categories are,

1) Primary sources of data

2) Secondary sources of data

Primary Sources of Data: \

Primary data are collected during the course of doing experiments in an experimental research but in case

research is done of the descriptive type and perform surveys, whether sample surveys or census surveys,

primary data can be obtained either through observation or through direct communication with respondents in one form.or another or through personal interviews.

Secondary Sources of Data:

In most of the studies the investigator finds it impracticable to collect first-hand information on all related issues and as such he makes use of the data collected by others. There is a vast amount of published information from which statistical studies may be made and fresh statistics are constantly in a state of production.

Execution of the Project

The researcher should see that the project is executed in a systematic manner and in time. If the survey is to be conducted by means of structured questionnaires, data can be readily machine-processed. In such a situation, questions as well as the possible answers may-be coded. If the data are to be collected through interviews, arrangements should be made for proper selection and training of the interviewers. The training may be given with the help of instruction manuals; which explain clearly the job of the interviewers at each step. Occasional field checks should be made to ensure that the interviewers are doing their assigned job sincerely and efficiently. , \

A careful watch should be kept for .unanticipated factors in order to keep the survey as much realistic a possible. This means that steps should-be- taken to ensure that the. survey is under statistical control so that the collected information is in accordance with the pre-defined standard of accuracy. '

Analysis of Data

After the data have been collected, the researcher turns to the task of analyzing them. The analysis of data requires a number of closely related operations such as establishment of categories, the application of these categories to raw data through coding, tabulation and then drawing statistical inferences. Researcher should classify the raw data into some purposeful and usable categories.

1) Coding operation is usually done at this stage through which the categories of data are transformed into

symbols that may be tabulated and counted.

2) Editing is the procedure,that improves the quality of the data for coding. With coding the stage is ready for tabulation.

3) Tabulation is a part of the Technical 'procedure where in the classified data are put in the form of tables.

Analysis work after tabulation is generally based on the computation of various percentages, coefficients, etc., by applying various well-defined statistical formulae.

In order to derive meaningful results from statistical tables,follow steps: I'1) The first step is to calculate relevant measures of-central tendency as also of dispersion, highlighting the major

aspects of the data.

2) The second step is to cross tabulate the data to ascertain some,useful relationships.

3) The third step is to calculate the correlation coefficient and undertake a regression analysis between variables. '

4) The fourth step is to undertake a multivariate analysis. Such an analysis used a variety of techniques to determine important relationships amongst several variables.

Testing of Hypothesis

After analyzing the data the researcher has to test the hypothesis, various tests, such as Chi-square test, t-test, F test, have been developed by statisticians for the purpose. The hypothesis may be tested through the use of one or more of such tests, depending upon the nature and object of research inquiry. Hypothesis testing will result in either accepting the hypothesis or in rejecting it. If the researcher had no hypothesis to start with, generalizations established on the basis of data may be stated as hypothesis to be tested by subsequent researches in times to come.

Procedure of Testing of Hypothesis

Step 1) Set up a Hypothesis: In the research process setting of hypotheses is done at the third step of the process. Then we collect sample data produce sample statistics, and use this information to decide how likely it

is that our hypothesized population parameter is correct.

Step 2)Set up a Suitable Significance Level:Having set up the hypothesis, the next step is to test the validity 'of Ho against that of H at a certain level or significance. The hypotheses are tested on a pre determined level of significance and as such the same should be specified. Generally, in practice, either 5% level or 1% level is adopted for the purpose.

The factors that affect the level of significance are:

i) The magnitude of the difference between sample means;

ii)The size of the samples;

iii)The variability of measurements within samples; a iv) Whether the hypothesis is directional or non-directional. A directional hypothesis is one which predicts the direction of the Difference between, say, means). In brief, the level of significance must be adequate in the context of the purpose and nature of enquiry .

Step 3) Test Statistic: The next step is to compute an appropriate test statistic which is based on an appropriate probability distribution. It is used to test whether the null hypothesis set-up should be accepted or rejected. For this purpose, we use, Z distribution under normal curve for large sample where the sample size is equal to or larger

than 30(n <30) and the distribution for small sample where the sample size n, less than 30 (n < 30).

Step 4) Doing Computations:Having taken the first three steps, we have completely designed a statistical test. We now proceed to the fourth step - performance of various computations - from a random sample of size n, necessary for the test. These calculations include the testing statistic and the standard error of the testing statistic.

Step 5) Making Decision: Lastly, a decision should be arrived as to whether the null hypothesis is to be accepted or rejected. In this regard the value of the test statistic computed to test the hypothesis plays a very important role. If the computed value of the test statistic is less than the critical value, the computed value of the test statistic falls in the acceptance region and the null hypothesis is accepted. If the computed value of the test statistic is greater than the critical value, the computed value of the test statistic falls in the rejection region and null hypothesis is rejected. Usually 5% level of significance a = 0.05 is used in testing a. hypothesis and taking' a decision unless otherwise any other level of significance is specifically stated.

Types of Test of Hypothesis

Tests of hypotheses can be divided into two categories:

1) Parametric Tests: Parametric methods make assumptions about the underlying distribution from which sample populations are selected. In a parametric test a sample statistic is obtained to estimate the population parameter. Because this estimation process involves a sample, a sampling distribution, and a population, certain parametric assumptions are required to ensure all components are compatible with each other.

Some of the important parametric tests include,

Z-test: Prof. Fisher has given a method of testing the significance .of the correlation coefficient in small samples. According to this method the coefficient of correlation is transformed into Z and hence the' name Z transformation. The statistic Z given by Prof. Fisher is used to test:

a) Whether an observed value of r differs significantly from some hypothetical value, or

b) Whether two sample values of r differ significantly.

For testing whether r differs significantly from zero, the t-test is preferable.

The Z-test compares sample and population means to determine if there is a significant difference. It requires a simple random sample from a population with a Normal distribution and where mean is known.

Z Test is applicable to both large and small samples.

i) t -Test: Ifwe take a very large number of small samples from a population and calculate the mean for each sample and then plot the frequency distribution of these means the resulting sampling distribution would be the Student's t-distribution.

The greatest contribution to the theory of small samples was made by Sir William Gossett and R.A. Fisher. Gossett published his discovery in'1905 under the pen name 'students' and it is popularly known as t-test or students' t-distribution or students' distribution.

When the sample size is 30 or less and the population standard deviation is unknown, we can use the tdistribution,

iii) F-Test Variance RatioTest:The object of the F-test is to discover whether the two independent estimates of population variance differ significantly, or whether the two samples may be regarded as drawn from the normal population having the same variance. '

Non-ParametricTests:As the name implies, non-parametric tests do not require parametric assumptions because interval data are converted to rank-ordered data. Handling of rank-ordered data is considered strength of non-parametric tests.

All practical data follow normal distribution. Under such situations, one can estimate the parameters such as mean, variance etc., and use the standard tests, they are known as parametric tests. The practical data may be non-normal and/or it may not be possible to estimate the parameter(s) of the data. The tests which are used for such situations are called nonparametric tests. Since, these tests are based on the data which are free from distribution and parameter; these tests are known as nonparametric tests.

The nonparametric tests require less; calculation, because there is no need to compute parameters. Also, these tests can be applied to very small samples"more specifically during pilot studies in market research.

Some ofthe important non-parametric tests include,

i)Chi-Square Test (Xl):distribution when the null hypothesis is true, or any in which the probability distribution of the test statistic (assuming the null hypothesis is true) can be made to approximate a chi-square distribution as closely as desired by making the sample size large enough.

ii) Sign Test: The sign test is the simplest of the non-parametric tests. Its name comes from the fact that it is based on the direction (or signs for pluses or minuses) of a part of observations and not on their numerical magnitude.

In any problem in which sign test is used, we count:

Number of + signs

Number of - signs

Number of 0's (i.e., which cannot be included either as positive or negative)

iii) Median Test:The Median Test is used to test for location differences between two or, more independent populations.

The Median Test does not take into account the distance from the median. It, like the Sign Test, only takes .into account which side of the median the observations lie on.

iv) Kolmogorov-SmirnovTest:A test for common distributions using a form of ordering other than the ranking system. This ordering is not based on the median data point.

v) Runs Test:A number of methods have been developed for judging the randomness ofa sample on the basis of the order in which the observations are taken. It is possible to determine whether the samples that look suspiciously non-random may be attributed to chance. The technique discussed below,is based on the theory of runs. A run is a succession of identical letters (or other kinds of symbols) which is followed or preceded by different letter or no letters at all.

Generalization and Interpretation

If a hypothesis is tested and upheld several times, it may be possible for the researcher to arrive.at generalization,i.e., to build a theory. If the researcher had no hypothesis to start with, he might seek to explain his findings on the basis of some theory. It is known as interpretation. The process of interpretation may quite often trigger off new questions.which in turn may lead to further researches.

Preparation of the Report or the Thesis . ,

Although report writing needs some skill, which can be developed with practice, the researcher should follow the main principles of writing a report. Some of these principles are:

1) There should be objectivity, coherence, clarity in the presentation of ideas

2) Report should be written in a concise and objective style in simple language avoiding vague expressions such as 'it seems,' 'there may be', and the like.

3) Charts and illustrations in the main report should be used only if they present the information .more clearly and forcibly.

4) Calculated 'confidence limits' must be mentioned and the various constraints experienced in conducting research operations may as well be stated.

5) The layout of the report should be as follows:

i) The preliminary pages;

ii) The main text, and

iii) The end matter.

In its preliminary pages, the report should carry title and date followed by acknowledgements and foreword. Then there should be a table of contents followed by a list of tables and list of graphs and charts, if any, given in the report.

The main text of the report should have the following parts:

1) Introduction: It should contain a clear statement of the objective of the research and an explanation of the methodology adopted in accomplishing the research. ,

2) Summary of Findings: A statement of findings, and recommendation in non-technical language should be there after introduction. If the findings are extensive, they should be summarized.

3) Main Report:The main body of the report should be presented in logical sequence and sections.

4) Conclusion: At the end of the main text, result of the research should be put clearly and precisely.

At the end of the report, appendices should be enlisted in respect of all technical data. Bibliography, i.e., list of books, journals, reports, etc., consulted, should also be given in the end. Index should also be given specially in a published research report.

Q) Define Research Design and explain the importance and need for Research Design

Meaning and Definition of Research Design

A research project conducted scientifically has' a specific framework of research from the problems identification to the presentation of the research report. This framework of conducting research is known as the research design.

A research design is simply the framework or plan for a study that is used as a guide in collecting and analyzing the data. It is blueprint that is followed in 'completing a study".

According to Kerlinger, "Research design is the plan, structure, and strategy of investigation conceived so as to obtain answers to research questions and 'to control variance.

According to Green and Tull, "A research design is the specification of methods and procedures for acquiring the information needed. It is the over-all operational pattern or framework of the project that stipulates what information is to be collected from which sources by what procedures".

A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research purpose with economy in procedure.

Features of Research Design

1) Objectivity: The objectivity of the procedure (either collection of data or scoring of the responses or both) may be judged by the degree of agreement between the final scores assigned to different individuals by more than one independent observer. The more subjective the observation,recording and evaluation of the responses, the less the different observers agree. It is therefore, any research design should permit the use of measuring Instruments which are fairly objective in which every observer or judge seeing a performance arrives precisely.

This ensures the objectivity of the collected data which will be used for analysis and findings.

2) Reliability: It is not easily tested by either by the multiple-form or the split-half technique. The test re-test approach is the most effective measure of reliability as it refers to 'consistency' throughout a series to measurements. Suppose, if a respondent gives a response to a question he is expected to give the same response to that question whenever he is asked in other form. But if the respondent keeps on changing his responses to the same type of question then the interviewer will be facing a difficulty in considering which one of there responses is genuine. The researcher should frame this question in such a way that the respondent cannot but give only one genuine response. Though there are some methods in determining the reliability of the responses given out by a respondent like.

3) Validity: As in the case of reliability there are a good number of procedures for establishing the validity of test, such as validating the present data against a concurrent criterion or a future criterion or a theory, etc. However; any measuring instrument is said to be valid when it measures what it propose to measure.

4) Generalization: The -next important aspects of a good research design is to ensure that the measuring instruments used in a research investigation yield objective, reliable and valid data and has to answer the 'generalization' of the findings. It will thus help an investigator in his attempt to generalize the findings, provided he has taken due care in defining the population, selecting the sample and using the appropriate statistical analysis while planning his research design.

Need for Research Design:

1)It facilitates the smooth sailing of the various research operations, thereby making research as efficient as possible yielding maximal information with minimal expenditure of effort, time and money.

2) Research design or a plan is needed in advance of data collection and analysis for research project.

3)Research design, in fact, has a great bearing on the reliability of the results arrived at and as such constitutes the firm foundation of the entire edifice of the research work.

4) The design helps the researcher to organize his ideas in a form whereby it will be possible for him to look

for flaws and inadequacies.

Purpose of Research Design

Any research design has two basic purposes:

To provide answers to research-questions as validly, objectively,accurately,and economically as possible, and To bring empirical evidence to bear on the research problem by controlling variance.

The above purpose of research design can further be explained as follows:

Accurate Results: All the research activities have the purpose of answering research questions. However, the manner of seeking answers to the research questions differ from situation to situation according to the nature of the problems. In any project the research problems are further stated in forms of specific hypothesis so that they can be tested against empirical evidences achieved. The hypothesis states the relationship between variables and may vary from being most general to most specific ones. There are various ways of testing the hypothesis depending upon their structure. This has resulted to the development of different designs of research.

Control of Variance: Second basic purpose of research design is the control of variance. Research designs help in manipulation of experimental variables, i.e., in seeking and establishing the relationship between the assumed cause or the experimental variable and the effect, i.e., the dependent variable. To establish such a relationship it is essential that the effect of other variables, besides the experimental one, should be controlled. Such variables are known as extraneous variables. By stating that the purpose of any research design is to control variance it is meant specifically for:

i)Maximize Systematic Variance:The systematic variance is the variation or the difference caused in the dependent variable by the; experimental variable alone and not by any other variable. By maximizing the' systematic variance means to magnify or make evident the effect of the experimental variable on the dependent variable. The concept of variance and its control can be explained further on the basis of an example.Suppose a professor of sociology, or an university administrator wants to improve the students, performance in the class.

For this he has to find a better method of imparting education. He makes the hypothesis that students' reading habit is increased or their class performance is improved by the 'Participation Method', i.e., by participating in the class discussions or seminars than by simple lecture method. In this example the experimental variable will be 'Participation Method of Teaching', the effect of which the professor or the administrator desires to measure, as compared to the effects of Lecture Method of Teaching. Students' performance is the dependent variable. In another study students' reading habit can be taken as the dependent variable, the experimental variable being the same.

ii) Control or Eliminate Extraneous Variance:It means the control or elimination of the impact of other independent variables, which are likely to influence the dependent variable but are considered as unwanted or extraneous in the context of particular research work. It is essential to eliminate their Impact so that variation in the dependent variable takes place only because of the assumed cause. In case of the above example age, intelligence, previous school environment, family background etc.,are the additional factors which might influence the reading habit or the class performance of the students.

The researcher's job is to isolate, minimize, nullify or eliminate the effect of such extraneous variables in order to demonstrate the effect of experimental variable 'teaching methods', on the dependent variable, 'the students' class performance or the students' 'reading habit'.

iii) Minimize Error Variance: A third group of factors, influencing the dependent variable are known as random variables because they are temporary factors which vary from situation to situation. Their influence is considered as error variance. There are a number of determinants of error variance, for example, factors associated with individual differences among subjects due to errors of measurement, variation of response from one trial to another,

guessing, momentary in attention, temporary fatigue, lapses of memory, and transient emotional state of subjects. Minimization of error variance can be achieved through:

a) Measuring under controlled conditions, and

b) By increasing the reliability of measure or measuring instruments.

3) Replicate the Study:To make study, in so far as possible, replicable, i.e, worth repeating. This can be done by avoiding situations and procedures which are clearly unique.

4)Provides Blueprint: A researcher faces many problems like what sample is to be taken, what is to be asked, what method of data collection is to be used and so forth. Research plan minimizes all these problems of the researchers because all decisions are taken beforehand.

5)Facilitates Systematic Investigation:This refers to determining whether only one (or selected) cause out of many' causes is to be examined, only one (or a few selected) hypothesis is to be tested; only attitudes or students of one educational institution are to be studied and so on. Since the objectives are clear and the structure is also provided, systematic investigation is possible.

6) Visualizes and Forecasts Potential Problems:The researcher studies available (other) literature and learns about new/alternative approaches, For example, he gets an estimate of personnel required as investigator(s), cost, possible measurements of problems and so forth. Berger et al. have suggested following functions of designing research: .

i) It offers a guide that directs the research action, which reduces time and cost.

ii) It offers a systematic approach to the research operation, so that all steps are executed in the right sequence.

iii) It encourages co-ordination and effective organization,

iv) It helps in the use of resources effectively, avoiding errors and bias.

v) It enables the researcher to control the research operation most effectively, when research investigators are employed.

Components of Research Design

I) Title of the Study: Should be brief, precise, and project the scope in generalized terms.

2) Statement of the Problem: Should be unambiguous, precise, and the usage should be clear, simple, and concise.

3) Review of Previous Studies: Should' be a brief survey of a relevant literature in the subject concerned and presented subject wise and reviewed critically and pinpoint the stage from where further research is called for.

4) Definition of Concept or Theoretical Principles involved if any: Should be defined in general terms and be linked with the study.

5) Coverage and Scope of the Study: Should consider, geographical, temporal, and functional dimensions.

6) Objectives of the Study: Should explain the main purpose precisely and may be in the form of questions or an explanation to a particular issue.

7) Formulation of Hypothesis: Should be empirical, conceptually clear, specific, close to things observable and related to the body of theory.

8) Methods of Investigation: It depends upon the nature of study but researcher should define survey m,ethodology, and statistical techniques adopted.

9) Sampling Design: Definition of the universe or population, size of the sample, and representativeness of the sample should be defined.

10) Constructing of Schedule or Questionnaire: Questions should be in an order on a form. Open ended questions are designed to permit a free response. The questions to be asked should have a direct bearing on the problem, avoiding the personal questions and multiple meanings.

11) Data Collection: Depends up the subject matter, the unit of enquiry and the scope of the study.

j •

12) Analysis of Data: To fulfill the objective or hypothesis the researcher should analyze the data subject to the appropriate

statistical analysis besides tabulation. Tabulation of results in a: meaningful way is by itself a technique and an art. The data given in the tables must be in a self-explanatory form.

13) Interpretation of Results: Researcher should draw inferences based on usual test for significance and relate with previous fmdings, to a wider field of generalizations, to scientific objectivity, and to uncover any additional factors which would not be visualized by the investigator earlier.

14) Reporting the Findings: Should be clear, specific, simple, and directly relating to the objective of the study. Researcher must report that what has been discovered or innovated to fulfill the need for which the study was taken up and to ensure proper directions to other researchers in carrying out similar researches.

Requirements for a Good Research Design

1) Well.Defined Problems: Nature and scope of the problem to be studied must be stated clearly, or say must be well defined and formulated. '

2) Clarity in Formulation: If any hypothesis is to be tested it must be clearly formulated.

3) Testable: The research design must adequately answer the research questions. And test the hypothesis.

4) Identifying Variables: Relevant variables must be clearly identified and operationalized. Adequate methods of collecting the information and inethods of logically deriving the conclusion must be developed. Only then control of variance is possible.

5) Serve the Validity Needs: The.research design must be structured in a manner that it fulfils the need of interna1and external validity.

Types of Research Design

The marketing research designs are classified on the basis, of the fundamental objective of the research. They may be exploratory or conclusive as depicted in figure

I) Exploratory Research I

i) Literature Research /Study of

Secondary Data

ii) Survey of knowledgeable persons

or-experience survey iii) Case study

iv) Focus Groups

v) Two-Stage Design, vi) Projective techniques

2) Conclusive Research

i} Descriptive

a) Longitudinal study

b) Cross-sectional study

ii) Causal Research

Exploratory Research Design:Exploratory research studies are also termed as formulative research studies. The main purpose of such studies is that of formulating a problem for more precise investigation or of developing the working hypotheses from an operational point of view. The major emphasis in such studies is on the discovery of ideas and insights. As such the research design appropriate for such studies must be flexible enough to provide opportunity for considering different aspects of a problem under study.

Exploratory research provides insights into and comprehension of an issue or situation. It should draw definitive conclusions only with extreme caution. Exploratory research is a type of research conducted because a problem a as not been clearly defined. Exploratory research helps determine the best research design, data collection method and selection of subjects. Given its fundamental nature, exploratory research often concludes that a perceived problem does not actually exist;

Exploratory research often relies on secondary research such as reviewing available literature andlor data, or qualitative approaches such as informal discussions with consumers, employees, management or competitors,

Reporting the Findings:Should be clear, specific, simple, and directly relating to the objective of the study. Researcher must report that what has been discovered or innovated to fulfill the need for which the study was taken up and to ensure proper directions to other researchers in carrying out similar researches.

Q) Define Sampling and Explain the steps in Sampling Design

Sampling design specifies for every possible sample its probability of being drawn.

Mathematically, a sampling design is denoted by the function p(s) which gives the probability of drawing a sample S.

p(s) is given by, .

p(S)=qN_",<S)x(l-q) ,Nror_N_",<Sl}

where,

q = Probability of being included in the sample for each element

Nsample(Ss) =Total number of elements in the sample S

Npop =Total number of elements in the population (before sampling commenced).

Characteristics of Good Sample Desig

I)Goal Orientation: This suggests that a' sample design "should be oriented to the research objectives, tailored to the survey design, and fitted to the survey conditions". If this is done, it should influence the choice of the population, the measurement as also the procedure of choosing sample.

2)Measurability: A 'sample design should enable the computation of valid estimates of its sampling, variability. Normally, this variability is expressed in the form of standard errors in surveys. However, this is possible only in the case of probability sampling. In non-probability samples, such as a quota sample, it is not possible to know the degree of precision of the survey results.

3) Practicality: This implies that the sample design can be followed properly in the survey. It is necessary that complete, correct, practical and clear instructions should be given to the interviewer so that no mistakes are made in the selection of sampling units and the final selection in the field is not different from the original sample design. Practicality also refers to simplicity of the design, i.e., it should be' capable of being understood and followed in,actual operation of the field work.

4)Economy: Finally, economy implies that the objectives of the survey should be achieved with minimum cost and effort. Survey objectives are generally spelt out in terms of precision, i.e. the inverse of the variance of survey estimates. For a given degree of precision, the sample design should give the minimum cost. Alternatively, for a given per unit cost, the sample design should achieve maximum precision (minimum variance)

5) Independence: Each element of universe is independent. Each element has equal chance of selection.

6) Homogeneity: There should not be any change in that universe where survey is conducted i.e. quality and nature of units should remain same.

7)Adequacy: Sample should be adequate. Too much low unit will not be desirable nor will too many high sampling units need more time and money for analysis.

Steps in Sampling Design

While developing a sampling design, the researcher must pay attention to the following points:

1)Type of Universe: The first step in developing any sample design is to clearly define the set of objects, technically called the universe, to be studied. The universe can be finite or infinite. In fmite universe the number of items is certain, but in case of an infinite universe the number of items is infinite, i.e., we cannot have any idea about the total number of items. The population of a city, the number of workers in a factory and the like are examples of finite universes, whereas the number of stars in the sky, listeners of a specific radio programme, throwing of a dice etc. are examples of infinite universes.

2)Sampling Unit: A decision has to be taken concerning a sampling unit before selecting sample. Sampling unit may be a geographical one such .as state, district, village, etc., or a construction unit such as house, flat, etc., or it may be a social unit such as family, club, school, etc., or it may be an individual.

3)Source List: It is also known as 'sampling frame' from which sample is to be drawn. It contains the names of all items of a universe (in case of finite universe only). If source list is not available, researcher has to prepare it. Such a list should be comprehensive, correct, reliable and appropriate. It is extremely important for the source list to be as representative of the population as possible.

4) Size of Sample: This refers to the number of items to be selected from the universe to constitute a sample.

This is a major problem before a researcher. The size of sample should neither be excessively large, nor too

small. It should be optimum. An optimum sample is one which fulfills the requirements of efficiency, representativeness, reliability and flexibility.

5)Parameters of Interest: In determining the sample design, one must consider the question of the specific population parameters which are of interest. For instance, we may be interested in estimating the proportion of persons with some characteristics in the population, or we may be int~d in knowing some average or the other measure concerning the population. There may also be important sub-groups in the population about whom we would like to make estimates. All this has a strong .impact upon the sample design we would accept.

6)Budgetary Constraint: Cost considerations, from practical point of view, have a major impact upon decisions relating to not only the size of the sample but also to the type of sample. This fact can even lead to the use of a non-probability. sample.

7)Sampling Procedure:Finally, the researcher must decide the type of sample he will use i.e., he must decide about the technique to be used in selecting the items for the sample. In fact, this technique or procedure stands for the sample design itself. There are several sample designs out of which the researcher must choose one for his study. Obviously, he must select that design which, for a given sample size and for a given cost, has a smaller sampling error.' '

Q) Explain the various SAMPLING METHODS

There are different types of sample designs based on two factors viz., the representation basis and the element selection technique. On the representation basis, the sample may be probability sampling or it may be non-Probability sampling. Probability sampling is based on the concept of random selection, whereas non-probability sampling is 'non-random' sampling. On element selectionbasis, the sample may be either unrestricted or restricted.

when each sample element is drawn individually from the population at large, then the sample so drawn is known asunrestricted sample where as' all other forms of sampling are covered under the term 'restricted sampling'.

Thus, sample designs are basically of two types viz., non- probability sampling and probability sampling as own in figure 2.2.

.

Probability Sampling.

Probability sampling is also known as 'Random sampling' or 'chance sampling'. Under this sampling design, every item of the universe has an equal chance of inclusion in the sample. It is, so to say, a lottery method in which individual units are picked up from the whole group not deliberately but by some mechanical process. Here it is blind chance alone that determines whether one item or the other is selected.

The results obtained from probability or random sampling can be assured in terms of probability i.e., we can measure the errors of estimation or the significance of results obtained from a random sample, and this fact brings out the superiority of random sampling design over the deliberate sampling design.

Advantages of Probability Sampling

1) Probability (Random) sampling is the only sampling method that provides essentially unbiased estimates

having measurable precision. If the investigator requires this level of objectivity, then some variant of probability sampling is essential.

2) Probability Sampling permits the researcher to evaluate, in quantitative terms, the relative efficiency of alternate sampling techniques in a given situation. Usually this is not possible in non-probability sampling.

3) This requires relatively little universe knowledge. Essentially, only two things need to be known:

i) A way of identifying each universe element uniquely, and

ii) The total number of universe elements.

"

If, in area sampling, a correspondence can be established between area units and universe items and area maps are available, then probability sampling can be used. In contrast, non-probability sampling methods may require substantial information.

Disadvantages of Probability Sampling

1) It is relatively expensive than non-probability sampling.

2) The method of selection in many cases can be complex and time consuming. Specially in the .cases of marketing research,the constraints of budget and time may give preference to non-probability methods of sampling.

Types of Probability Sampling

The various probability sampling methods are as follows:

1) Simple Random Sampling

2) Systematic Sampling

3)StratifiedSampling

4)Clusters Sampling

5) Multi-Stage Sampling

6) area sampling SimpleRandom Sampling

This is the simplest and most popular technique of sampling. In it each unit of the population has equal chance of being included in the sample.This method implies that if N is the size of the population and n units are to be drawn in the sample, then the sample should be taken in such a way that each of the NCn samples has an equal chance of being selected.

Simple random sampling gives:

1) Each element in the population an' equal chance of being included in the sample and all choices are independent of each other.

2)Each possible sample combination an equal chance of being chosen.

the method of simple random sampling eliminates the chance of, bias or personal prejudices in the selection of units.

Methods of Simple Random Sampling

Some of the common methods of drawing simple random samples are:

1)Lottery Method: The following are the steps in this 'method, Let N be the size of population and a sample of size n is to be drawn.

i)Number the units of the population from 1 to N. .

ii) Take N identical pieces of papers, cards, capsules or balls and number these from 1 to N.

iii)Mix these thoroughly in a bag, bowl or some other container and pick out n items either one by one or in one stroke blind folded. :

iv)The number of units in the population bearing the numbers on the items drawn in step will constitute the desired random sample.

Though the method is simple and easy to apply, but incase the size of the population is infinite, the method becomes unmanageable. -

By Using Random Numbers:A number of people viz., L.R.C. Tippet, Fisher and Yates, Kendall and Smith, Oliver and Boyd and Rand Corporation constructed set of random numbers. These numbers can be used to select random samples from a given population. A table of true random numbers is one in which any digit from 0 to 9 have an

equal chance of appearing in any position of the table. Random numbers are most useful when population is of infinite size. The digits in random number tables are selected at random and are arranged independently of digits occupying other places in a number. The random number table prepared by L.H.C. Tippet contains a set of 10400 four figure numbers.

advantages of Simple Random Sampling:

1)The method is objective.

2)The conclusions can be derived in terms of probability or errors of estimation.

3)Accurate mathematical tests may be applied to judge the randomness of the sampling method.

Disadvantages of Simple Random Sampling:

Cost: One factor limiting the use of simple random sampling is the cost. Because the method guarantees that every possible-item in the universe has the same chance of being chosen, the actual sample selected often consists of universe items that are widely dispersed geographically.If personal interviews are used, interviewers may have to travel considerable distances, thereby increasing the costs of the field operation.

Availability of a Current Listing of Universe Elements: A second serious limitation to practical use of simple random sampling is the need for an accurate list of universe elements.

Statistical Efficiency:A third difficulty associated with simple random sampling is that it is often statistically inefficient. One sample design is said to be statistically more efficient than another when, for the same size sample, a smaller standard error is obtained.

Administrative Difficulties:A number 'of difficulties are associated with the administration of simple random samples. One is the conceptually simple, but sometimes troublesome, problem of selecting the sample..

Another administrative problem in simple random sampling is the difficulty of maintaining supervisory control when using in-home personal interviews.

Stratified Sampling

Stratified sample is one in which random selection is done not from the universe as a whole but from different parts or strata of a universe.

This sampling procedure may be summarized as follows:

1) The universe to be sampled is divided (or .stratified) into groups that are mutually exclusive and include all items in the universe.

2) A simple random sample is then chosen independently from each group or stratum.

The process of stratified random sampling differs from simple random sampling in that, with the later, sample items are chosen at random from the entire-universe. In stratified sampling, the sample is designed so that a separate random sample is chosen from each stratum. In simple random sampling the distribution of the sample among strata is left entirely to chance. .

Formally, divide the population into non-overlapping groups(i.e.,strata) N1 ,N2·············Nj

Such that N1+ N2, + … … … … .+Ni=N

Then do a random sample of f=n/N in each strata where f is the sampling fraction .

To select Stratified Random Sample one has to consider:

1) Base of Stratification: Strata are created on the basis of a variable known to be correlated with the variable of interest and for which information on each universe element is known. Strata should be constructed in a way which will minimize differences among sampling units within strata, and maximize difference among strata.

The purpose of stratification is to increase the efficiency of sampling by dividing a heterogeneous universe in such. a way that:

i) There is as great a homogeneity as possible within each stratum, and ii) A marked difference is possible between the strata.

2) Number of Strata: The practical considerations limit the number of strata that is feasible, costs of adding more strata may soon outrun benefits. As a generalization more than six strata may be undesirable.

3) Sample Size with in Strata: We can use either a proportional or a disproportional allocation. In proportional allocation, one samples each stratum in proportion to its relative weight. In disproportional allocation this is not the case. It may be pointed out that proportional allocation approach is simple and if all one knows about each stratum is the number of items in that stratum; it is generally also the preferred procedure. In disproportional sampling, the different strata are sampled at different rates. As a general rule when variability among observations within a stratum is high, one samples that stratum at a higher rate than. for strata with less internal variation.

For example, suppose a researcher wishes to study retail sales of a product such as wheaties in a universe of 100,000 grocery stores. The researcher might first subdivide this universe into three strata, based on store size, as illustrated below:

Store Size Stratum Number of Stores Percentage of storesLarge stores 20,000 20Medium stores 30,000 30Small stores 50,000 50Total 1,00,000 100

Then, by random sampling independently within each of the three strata, the researcher could guarantee the desired sample allocation of stores within each size group- instead of leaving their representation to chance,

For example, suppose it were desirable to have total samples of 120 stores, split equally among the three size strata

that is, 40 stores from each stratum. With the stratification scheme shown, the researcher would simply choose 40 stores at random from each stratum. Without stratification, simple random sampling from the entire miverse would be expected to yield about 24 large stores (20 percent of 120); about 36 medium stores (30percent of 120); and about 60 small stores (50 percent of 120).

Advantages of Stratified Sampling

More Representative:This is particularly so when the universe is heterogeneous.By stratifying the universe, in homogenous groups the element of heterogeneity is reduced in -the sense that different strata take care of the heterogeneity of the universe and the chance of any particular element of heterogeneity being prominent in the sample is ruled out. When same sampling fractions (f) within the strata then it is called proportionate stratified random sampling.When different sampling fractions (f) within the strata then it is called disproportionate stratified random sampling.

Certainty:This type of sampling balances the uncertainty of random sampling against bias of deliberate selection.

Greater Precision:Since variability in each stratum is reduced, stratified random sampling provides more precise estimates than those provided/by simple random sampling.

Administrative Convenience: Division of the universe into different strata of sub-groups result in administrative convenience.

advantages of Stratified Sampling

Strarified random sampling suffers from the difficulties of assigning weights to different strata and if the weights are not properly assigned, inferences drawn become misleading.

There are difficulties in stratification of the universe into homogeneous groups and also in determining appropriate size of the samples to be drawn from each s t r a t u m . .. ~',

Systematic Sampling

In this form of sampling one unit is selected at random from the universe and the other units are at a specified interval from. the selected unit. This method can be used when the population is finite-and the 'units of the Universe can be arranged on the basis of any system like alphabetical arrangement,numerical arrangement or geographical arrangement etc. -

Procedure of a Systematic Sampling

A systematic sample can be selected from a list of universe items using. a four-step procedure:

1)The first step is to determine the total number of items in the universe. Divide (his figure by the desired sample size. The result is called the sampling interval.

2) Select a random number between 1 and the sampling interval figure. This identifies the first element on the universe list to be included in the sample.

3) Add the sampling interval to the random number selected in step (b). The total represents the second element on the universe list. to be included in the sample.

4) Continue adding the sampling interval to each total to create a new total.Each new total represents another element on the universe list to be included in the sample.

Advantages Of Systematic Sampling

1) This system is very simple and convenient;

2) Results obtained by it are generally satisfactory. . I

3) If the population is large systematic sampling would give us results which will be similar to those obtained by proportionate stratified random sampling,

Disadvantages of Systematic Sampling

1) The. systematic sampling may select only one cluster of the population although there may be several clusters in the universe. The sampling error, therefore, may be very high and cannot be evaluated properly.

2) It may be possible to obtain an unbiased estimate of the sampling error by drawing a number of systematic samples instead of one.

3) There may be a possibility of selecting impracticable units of the population. In a practical situation, it may be easy to determine whether a periodicity is present or to evaluate its significance.

Cluster Sampling

In this method, the universe is divided into some recognizable sub-groups which are called clusters. After this a simple random sample of these clusters is drawn and then all the units belonging to the selected clusters constitute the sample.

For example, if we have to conduct an opinion poll in the city of Delhi, then the city may be divided into, say,50 blocks and out of these 50 blocks 5 blocks can be picked up by random sampling and the inhabitants in these five blocks can be interviewed to give their opinion on a particular issue.

While using this method, it should be seen that clusters are of as small a size as possible and the number of sample units in each cluster should be more or less the same. This method is commonly used in collecting data about some common characteristics of the population.Cluster sampling, no doubt, reduces cost by concentrating, surveys in selected clusters. But certainly it is less precise than random sampling. There is also not as much information in n'observations ,within a cluster as there happens to be in 'n' randomly drawn observations. Cluster sampling is used only because of the economic advantage it possesses; estimates based on cluster samples are usually more reliable per unit cost.

Multi-Stage Sampling

This is a modified form of cluster sampling. While in cluster sampling all the units in a selected cluster constitute the sample, in multistage sampling the sample units are selected in two or three or four stages. In this system the universe is first divided into first-stage sample units, from which the sample is selected. The selected first-stage samples are then sub-divided into second stage units from which another sample is selected. Third stage and fourth-stage sampling is done in the same manner if necessary.

Thus, for an urban survey, a sample of towns may be taken first and then for each of the selected town a sub sample of households may be taken, and then, if need be, from each of the selected household a third-stage sample of individuals may be obtained.

Advantage of Multi-Stage Sampling

There are two advantages of this sampling design viz.,

1) It is easier to administer than most single stage designs mainly because of the fact that sampling frame under multi-stage sampling is developed in partial units.

2) A large number of units can be sampled for a given cost under multistage sampling because of sequential clustering, whereas this is not possible in most of the simple designs.

Disadvantag of Multi-Stage Sampling

The principal disadvantage of "the system is that the quantum of errors in it may be large and variability of the

estimates in this method would depend on the composition of the primary and secondary units.

Area Sampling

Area Sampling is a form of multi-stage sampling in which maps, rather than lists or registers are used as the sampling frame. It is more frequently used in those countries which do not have a satisfactory sampling frame such as a population lists. If clusters happen to be some geographic subdivisions, in that case cluster sampling is better known as area sampling. In other words, cluster designs, where the primary sampling unit represents a cluster of units based on geographic area, are distinguished as area sampling. The plus and minus points of cluster sampling are also applicable to area sampling. The overall area for sampling is divided into several smaller areas within which a random sample is selected.

For example, the city map is used for area sampling. Various blocks provide the frame and each of them are numbered and used for the sampling. For sampling blocks stratification is employed, which is based on geographical considerations. Thus blocks are needed to be identified and then a stratified sample of dwellings zan be selected. Finally blocks are subdivided into segments -of a more or less equal size, and a sample of these segments may be taken in the sample.

Non-Probability Sampling

non-Probability sampling is that sampling procedure which does not afford any basis for estimating the probability that each item in the population has been included in the sample. Non-probability sampling is also mown by different names such as deliberate sampling, purposive sampling and judgment sampling.

In this type of sampling, items for the sample are selected deliberately by the researcher; his choice concerning the items remains supreme. In other words, under non-probability sampling the organizers of the inquiry purposively choose the particulars units of the universe for constituting a sample on the basis that the small mass that they select out of a huge one will be typical or representative of the whole.

Types of Non- Probability Sampling

The various non-probability sampling methods are: 1)Convenience Sampling

2) Judgment Sampling

3) Quota Sampling

4) Panel Sampling

5) Snowball Sampling

Convenience Sampling

In convenience sampling selection, the researcher chooses the sampling units on the basis of convenience or accessibility. It is called accidental samples because the sample- units enter by accident.This is also known as a sample of the man in the street, i.e., selection of units where they are. Sample units are selected because they are accessible.

For example, in testing a potential new product, the sample work is done by adding the new product to the appropriate shops in the locality. Purchasing and selling of the new product is observed there.

Judgment Sampling

A method of non-probability sampling that is sometimes advocated is the selection of universe items by means of expert judgment. Using this approach, specialists in the subject matter of the survey choose what they believe to be the best sample for that particular study. - For example, a group of sales managers might select a sample of grocery stores in a city that they regarded as "representative." This approach has been found empirically to produce unsatisfactory results. And, of course, there is no objective way of evaluating the precision of sample results. Despite these limitations, this method may be useful when the total sample size is extremely small.

Merits of Judgment Sampling

1) When only a small number of sampling units are in the universe, simple random selection may miss the

more important elements, whereas judgment selection would certainly include them in the sample.

When we want to study some unknown traits of a population, some of whose characteristics are known; we may then stratify the population according to these known properties and select sampling, units from each stratum on the basis of judgment. This method is used to obtain a more representative sample

2) In solving everyday business problems and making public policy decisions, executive.s and public officials are often pressed for time and cannot wait for probability sample designs. Judgment sampling is then the only practical method to arrive at solutions to their urgent problems.

Demerits of Judgment Sampling

Judgment sampling method is however associated with the following demerits:

1) Non-Scientific: This method is not scientific because The population units to be sampled may be affected by the personal prejudice or bias of the investigator. Thus, judgment sampling involves Ithe risk that the investigator may establish foregone conclusions by including those items in the sample which conform to his preconceived notions.

2) No Method to Calculate Sampling Error: There is any objective way of evaluating the reliability of sample results. The success of this method depends upon the excellence in judgment. If the individual making decisions is knowledgeable about the population and has good judgment, then theresulting sample may be representative, otherwise the inferences based on the sample may be erroneous. It may be noted that even if a judgment sample is reasonably representative, there is no objective method for determining the size or likelihood of sampling error. This is a big defect of the method.

Quota Sampling

One of the most commonly used non-probability sample designs is quota sampling, which enjoys its most widespread use in consumer surveys. This sampling method also uses the principle of stratification. As in stratified random sampling, the researcher begins by constructing strata. Bases for stratification in consumer surveys are commonly demographic, e.g., age, sex, income and so on. Often compound stratification is used - for example, age groups within sex. Next, sample sizes (called quotas) are established for each stratum. As with stratified random sampling, the sampling within strata may be proportional or disproportional. Field-workers are then instructed to conduct interviews with the designated quotas, with the identification of individual respondents being left to the field-workers.

Advantages of QuotaSampling

1) It is economical as traveling costs can be reduced. An interviewer need not travel all over a town to track down pre-selected respondents. However, if numerous controls are employed in a quota sample, it will become more expensive though it will have less selection bias.

2) It is administratively convenient. The labor of selecting a random sample can be avoided by using quota sampling. Also, the problem of non-contacts and call-backs can be dispensed with altogether.

3) When the field work is to be done quickly, perhaps in order to minimize memory errors, quota sampling is most appropriate and feasible.

4) It is independent of the existence of sampling frames. Wherever a suitable 'sampling frame is not available, quota sampling is perhaps the only choice available. '

DisadvantagesofQuota Sampling

1) Since quota sampling is not based on random selection, it is not possible to calculate estimates of standard

errors for the sample results. ,

2) It may not be possible to get a 'representative' sample within the quota as the selection depends entirely on

the mood and convenience of the interviewers.

3) Since too much latitude is given to the interviewers, the quality of work suffers if they are not competent.

4) It may be extremely difficult to supervise and control the field investigation under quota sampling.

Panel Sampling

Here the initial samples are drawn on random basis and information from these is collected on regular basis. It is a semi-permanent sample where members may be included repetitively for successive studies. Here there is a facility to select and quickly contact such well balanced samples and to have relatively high response rate even by mail.

Advantages of Panel Sampling

1)Lesser cost and time involved in the collection of information.

2)Due to fixed sample units, one can measure the changes in repeated reporting.

3)Shifts of behavior over time can be traced.

DisadvantagesofPanelSampling

1)The sample may not be fully representative.

2)The members of the panel may become conditioned to some specific situation

3)It may be difficult to preserve the representative character of the panel for a long time as the professional members of the panel may drop out voluntarily and may need replacement.

Snowball Sampling

It is a special non-probability method used when the desired sample characteristic is rare. It may be extremely difficult or cost prohibitive to locate respondents in these situations. Snowball sampling relies on referrals from initial subjects to generate additional subjects.While this technique can dramatically lower search costs,it comes at the expenseof introducing bias because the technique itself reduces the likelihood that the sample will represent a good cross section from the population.

Q) Explain the various methods of DATA COLLECTION

The task of data collection begins after a research problem has been defined and research design/plan chalked While deciding about the method of data collection to be used for the study, the researcher should keep in two types of data viz., primary and secondary.

The primary data are those, which are collected afresh and for the first time, and thus happen to be original in secondary data, on the other hand, are those which have already been collected by someone else and which have already been passed through the statistical process.

For the purpose of collecting data, a number of research instruments are used such as questionnaire, schedules etc. For adequacy and validity in research it is required that these instruments are designed properly. A high quality research instrument, should be not only well suited to the research requirement, but also designed to be as user friendly as possible. Instrument design also requires the expertise to design custom questions to meet specific and unique requirements.

Any statistical data can be classified under two categories depending upon the sources utilized. These categories are

1) Primary Data

2) Secondary Data

PRIMARY DATAPrimary data is-the one, which is collected by the investigator himself for the purpose of a specific inquiry or study. Such data is original in character and is generated by survey conducted by individuals or research institution or any organization.

The objectives of primary data are formulated on the basis of research objectives. Objectives set the guidelines and directions of research planning. Formulating the objectives offers the best feasible means of solution. The research study should yield measurements related to the research objectives as the measurements will provide directions for a decision.The findings of the research should be capable of being utilized for the better performance of the organization. The cost-benefits analysis should be made for determining the objectives of the primary data collection. .

Classification of Primary Data

I) Data Classified by their Nature: The nature of data may be classified according to various categories:

Facts,knowledge,opinions, intentions, motivation and behavior.

i) Facts:Facts refer to actuality but they not necessarily are material. The measurable facts can be measured precisely and definitely. The descriptive facts relating to people may be demographic and sociological. These characteristics represent the attributes of people, e.g., age, sex, income and level of education. The sociological data are related to how people are organized in and related to society.

ii) Knowledge:Knowledge refers to what people know. Potential buyers' knowledge and awareness of products or brands are important data of marketing research. The respondents, awareness and knowledge are evaluated to get sufficient data for marketing research.

iii) Opinions:Opinions are people's perceptions. What people think or what is in their minds are called opinions. Their perceptions mayor may not be true. Thus, they may be well defined as attitudes. These are products of mental sets and may be referred to as images.

iv) Intentions:Intentions are acts that are in the minds of people. These are expectations of behavior, or intentions to indulge in particular marketing behavior.

v)Motivation:Motivation is how to steer and direct people's actions. It is known as the inner state of mind that energizes activities and moves or directs the behavior of people.

2) Data Classified According to Function: Data are also classified according to. their functions. While planning data, the researchers anticipate the future analysis and synthesis according to their function. They try to avoid redundant data and collect necessary data. Data according to function may be causal, payoff, descriptive and classification. . i)Causal Data: Causal data reveal the cause and effect relationship. One hypothesis is measure in terms of

effects. Data required to measure the hypothesis are termed causal data. Such types of causal data are required in the marketing mix. They are used for experimental purpose in all the fields of marketing variables.

ii) Payoff Data:The payoffs are resultant data. They are the outcome of certain causal data, i.e., results of certain phenomenon.The causal variables are measured in terms of payoff or effects. This means that payoff data are required to measur,e the causal variables.

iii) Descriptive Data: There is need of such types of data, which may describe the situation',' statement and facts. Even in the case of experimental data, one variable requires to be controlled for which descriptive data are used. In such cases, a description of the samples is needed when drawing

conclusions.

iv) Classification Data: In sophistication experimental design the compound data have been' classified to arrive at simple analysis and conclusions. The classification data, i.e., the data classified -in' relevant categories are conceivable and may be easily described. The classification data in complexand multiple groups, i.e., more than one causal variable or rotation of treatments in sub-groups have' fiinctional utility. The sample survey also provides classification data, e.g according to age, sex,income, location etc.

> .-

Advantages of Primary data

1)Reliability:The information collected for primary data is more reliable than those collected, from

the secondary data because these informations are collected directly from the respondents.So ·these

carries higher rote of reliability.

2)Availabilty of a wide range:There are a lot of techiniques that can be employed,means that all information

necessary can be obtained through using the appropriate techiniques,enabling all areas of the research topic to

be answered and investigate throughly and effectively.

3)Addresses Specific Research Issues:Carrying-out their own research allows the marketing organization to address issues specific to their own situation. Primary research is designed to collect the information the marketer wants to know, and report it in ways that benefit the marketer.

4) Greater Control: Not only does primary research enable the marketer to focus on specific issues, it also enables the marketer to have a higher level of control over how the information is collected. In this way the marketer can decide on such issues as size of project (e.g., how many responses), location of research (e.g., geographic area), and timeframe for completing the project. 5)Efficient Spending for Information:Unlike secondary research, where the marketer may spend for information that is not needed, primary data collections' focus on issues specific to the researcher improves the chances that research funds will be spent efficiently.

6)Proprietary Information:Information collected by the marketer using primary research is their own and is generally not shared with others. Thus, information can be kept hidden from competitors, and potentially offer an "information advantage" to the company that undertook the primary research.

Disadvantages of Primary Data

1)Cost: Compared to secondary research,primary data may be very expensive since there is a great deal of marketer involvement, and the expense in preparing and carrying-out research can be high.

2)Time Consuming: To be done correctly primary data collection requires the development and execution of a research plan.Going from the start-point of deciding to undertake a research project to the end-point of having results is often much longer than the time it takes to acquire secondary data.

3)Not Always Feasible:Some research projects, while potentially offering information that could prove quite valuable, are not within the reach of a marketer. Many are just too large to be carried-out by all but the largest companies, and some are not feasible at all. For example, it would not be practical for McDonald's to attempt to interview every customer who visits their stores on a certain day since doing so would require hiring a huge number of researchers, an unrealistic expense. Fortunately, there are ways for McDonald's to use other methods (e.g:, sampling) to meet their needs without the need to talk with all customers.

4)Large Volume of Data: Since the data collected by primary methods remains in a very large amount so it becomes very complicated to handle and maintain all the-data. Large volumes of data also create difficulty in the data processing.

5)Reluctancy of Respondents:In many cases, the respondents remain reluctant to give the answers of the researchers' questions. Sometimes they give such answers which create biasness in the research.

Methods of Primary Data Collection

we collect primary data during the course of doing experiments in an experimental research but in case we do

research of the descriptive type and perform surveys, whether sample surveys or census surveys, we can obtain

primary data either through observation; or through direct communication with respondents in one form or

another or through personal interviews ..Thus, in other words, means that there are several methods of collecting

:rimary data, particularly in surveys and descriptive researches. Important ones are:

1) Observation method,

2) Interview method,

3) Questionnaire method and

4) Schedules

5) Other methods

i) Warranty card

ii) Distributor audits

iii) Pantry audits

iv) Panels/ Consumer Panels

. v) Mechanical devices

vi)Projective techniques

vii)Depth interviews, and

viii) Content analysis

Observation Method;

Observation is an activity of a person which senses and assimilates the knowledge of the phenomenon or the recording of data using' instrument. It can also be referred as datum collected during this activity. The observation method is the most commonly used method especially in studies relating to behavioral sciences. In a way we 'ali observe things around us, but this sort of observation is not scientific observation. Observation becomes a scientific tool and the method of data collection for the researcher, when it serves a formulated research purpose, is systematically planned and recorded and is subjected to checks and controls on validity and reliability. Under the observation method, the information is sought by way of investigator's own direct observation without asking from the respondent.

Observation is accurate watching and noting of phenomena as they occur in nature with regard to cause and effect or mutual relations. Thus, observation is not only a systematic watching but it also involves listening and reading, coupled with consideration of the seen phenomena.

Under this method, the researcher collects information directly through observation rather than through the reports of others. It is a process of recording relevant information without asking anyone specific questions and in some cases, even without the knowledge of the respondents.this method of collection is highly effective in behavioral surveys.

Observation can be:

1) Participant Observation Method:In this method the researcher joins in the daily life of informants or organizations and observes how they behave.

2) Non-Participant Observation Method:In this method the researcher will not join the informants or organizations but will watch from outside.

The observation method may be used to study:

1) Sales technique

2) Customer movement

3) Customer responses in retail stores.

4) Sock audit in retail stores for brands bought.

5) Pantry check in the kitchen of the housewife for brands bought.

6) Dust-bin check at the customer's house.

7) Poster research, counting the number of people passing by a poster.

8) Fashions and style acceptances.

Methods of Observation

1) Structured or Unstructured Observation: This observation is used when the research problem has been formulated precisely and the researcher is told to observe the area of study. The researchers are asked to record their observations. On the other hand unstructured observation implies that the researchers are free to observe whatever they feel relevant and judicious.

2) Disguised Observation: Here, the subject or informants do not know that they are being observed. This is preferred as it is feared that people may behave differently when they know that somebody is observing them. It is difficult to completely disguise an observation; it poses an ethical question of its desirability when those who are being observed are kept in dark.

3) Observation under Natural Setting-Laboratory Setting: Observations in field studies are in their natural setting and are studied in extremely realistic conditions. Sometimes, an experimental manipulation may be introduced in a field study. Observation in a laboratory setting, on the other hand, enables the observer to control extraneous variables, which influence the behavior of people. Observational studies in laboratory settings have certain advantages over field studies. They enable the collection of data promptly and economically and in addition, permit the use of more objective measurements.

4) Direct-Indirect Observation: In direct observation, the behavior of a person is observed. On the other hand indirect observation implies that same record of past behavior is observed, the behavior is not observed, and rather its effects are observed. Here the observer engaged in indirect observation generally looks for physical traces of behavior or occurrence of an event.

5) Human-Mechanical Observation: Here observations are done by manually or by machines. Most of the studies in marketing research are based on human observation where in trained observers are required to observe and faithfully record their observations. In some cases, mechanical devices such as eye cameras and audiometers are used for observation. One of the major advantages of electrical/mechanical devices is that their recordings are free from subjective bias. As against this advantage, such observations may be less valid than human observations. This is because the observer's power of integration can lead to a more valid evaluation of the observation.

Advantages of Observation Method

1) Superior in Data Collection on Non-Verbal Behavior: When a person's opinion on a particular issue is to be assessed,survey method is definitely more useful, but when the non-verbal behavior is to be discovered or where memory failure of the respondent is possible, observation will be more functional. It allows not the restrictive study of

the individuals but their in-depth study. The unstructured observational method, being very flexible, allows the observer to concentrate on any variables that prove to be important.

2)Intimate and Informal Relationship:Since the observer often lives with the subjects for an extended period of time, the relationship between them is often more intimate and more informal than in a survey in which the interviewer meets the respondents for 30-40 minutes on a very formal basis. The relationship sometimes becomes primary than secondary.Being close to the subject does not necessarily mean that observer will lose objectivity in recording facts. This becomes possible only when the observer becomes emotionally attached to the subject. ,

3)Natural Environment:The behavior being observed in natural environment will not cause any bias.Observation will neither be artificial nor restrictive. ' .

4)Longitudinal Analysis: In observation, the researcher IS able to conduct his study over a much longer period than in the survey. ' '

Limitations of Observation Method

Lack of Control: In artificial setting, control over variables is possible but in natural environment, the

researcher has little control over variables that affect the data.

Difficulties of Quantification:The data collected through observation cannot be quantified. The recorded data will show how persons interacted with one another but it cannot be completed the number of times they interacted. In communal riots, looting, arson, killing may be observed but it cannot be quantified what type of people indulged' in what? It is difficult to categories in-depth emotional and humanistic data.

Small-Sample Size: Observational studies use a smaller sample than survey studies. Two or more observers can study a bigger sample but then their observations cannot be compared. Since observations are made for a longer period, employing many observers can become a costly affair. '

Gaining Entry: Many times the observer has difficulty in receiving approval for the study. It is not always easy to observe the functioning of an organization or institution without obtaining permission from the administrator. In such cases, he ,may not record observations then and there but may write notes at night.

5) Lack of 'Anonymity/Studying Sensitive Issues:In observational study, it is difficult to maintain the respondent's anonymity. In survey, it is easy for the husband to say that he has no quarrels and conflicts with his wife but in observation over a longer period of time, he cannot conceal them.

6) Limited Study: All aspects of the problem cannot be observed simultaneously. The observation technique studies only limited issues. Similarly,' internal attitudes and opinions cannot be studied.

Interview Method

Interview is a conversation between two or more people where question are asked by the interviewer to obtain ' Information from the interviewee. The interview method of collecting data involves presentation of oral-verbal stimuli and reply in terms of oral-verbal responses. This method can be used through personal interviews and, if possible, through telephone interviews.

Interviewing is one of the prominent methods of data collection. It may be defined as a two-way systematic conversation between an investigator and an informant, initiated for obtaining information relevant to a specific study. It involves not only conversation, but also leaning from the respondent's gestures, facial expressions and pauses, and his environment.

Interviewing requires face-to-face contact or contact over telephone and calls for interviewing skills. It is done by using a structured schedule or an unstructured guide.

The interview method of collecting data involves presentation of oral-verbal stimuli and reply in terms of oral verbal responses. This method can be used through personal interviews and, if possible, through telephone interviews. '

Characteristics of Interviewing Method

I) Needs Proper Introduction: The participants - the interviewer and the respondent - are strangers. Hence, the investigator has to get himself introduced to the respondent in an appropriate manner.

2) Incorporates Transitory Relationships: The relationship between the participants is a transitory one.It has a fixed beginning and termination points. The interview proper is a fleeting, momentary experience fo: them.

3) Caters to a Specific Purpose: Interview is not a mere casual conversational exchange, but a conversation with a specific purpose, viz., obtaining information relevant to a study.

4) Verbal Interaction: Interview is a mode of obtaining verbal answers to questions put verbally.

5) Facilitates Telephonic Conversation: The interaction between the interviewer and the respondent need no: necessarily be on a face-to-face basis, because interview can be conducted over the telephone also.

6) Group Studies Possible:Although interview is usually a conversation 'between two persons, it need not be limited to a single respondent. It can also be conducted with a group of persons, such as family members, or a group of children or a group of customers, depending on the requirements of the study

7) Interactional Process: Interview is an interactional process. The interaction between the interviewer and the respondent depends upon how they perceive each other. The respondent reacts to the interviewer's appearance, behavior, gestures, facial expression and intonation, his perception of the thrust of the questions and his own personal needs. As far as possible, the interviewer should try to be closer to the socio-economic level of the respondents. Moreover, he should realize that his respondents are under no obligation to extend response. He should, therefore, be tactful and be alert to such reactions of the respondents as lame-excuse, suspicion, reluctance or indifference, and deal with them suitably. He should not also argue or dispute. He should rather maintain an impartial and objective attitude.

8) Simltaneous Recording: Information furnished by the respondent in the interview is recorded by the investigator. This poses a problem of seeing that recording does not interfere with the tempo of conversation. j

9) Flexible and Psychological Process: Interviewing is not a standardized process like that of a chemical technician; it is rather a flexible psychological process. The implication of this feature is that the interviewer cannot apply unvarying standardized technique, because he is dealing with respondents with varying motives and diverse perceptions. The extent of his success as an interviewer is very largely dependent upon his insight and skill in dealing with varying socio psychological situations

Types of Interview

1) Personal Interview:Personal or face-to-face interviewing is a core function of marketing research; much of the quality of the entire research process rests on its effectiveness. Despite the growth in' popularity of telephone and mailsurveys, personal' interviewing retains its long-held dominance across a wide spectrum of surveys - market, social, political. A personal interview is face-to-face communication with the respondent. The interviewer gets 'in touch with the respondent, asks the questions, and records the answers obtained. It is the interviewer's responsibility to record the answers either during the interview or after the interview. The main purpose of this consideration is that the answer must be recorded clearly and correctly. The personal interview may be either structured or unstructured. In a structured interview the formal questionnaire has been formulated and the questions are asked in pre-arranged order.

There may be other classifications ,of a personal interview on the basis of approaching the questions. It may either direct or indirect. In the case of indirect questions, the main questions are intentionally disguised. Thus, there may be four types of personal interview:

i) Structured and Direct Interviews: The usual type of interview is structured direct interview. A formal questionnaireconsisting of non-disguised questions are used for this interview. The main purpose is to get the facts. A formal list of questions is prepared and questions are asked in sequence. No other questions except from the

questionnaire are sought from the respondents. Answers are limited to a list of alternatives from which the respondents have to select the best answer.

ii) Unstructured and Direct Interviews:. The structured questions provide limited answers. Sometimes they give only two alternatives, i.e., yes or no, whereas the marketing management may desire to know the reasons for the facts and the phenomena. Direct questions in this case rarely elicit useful answers, diagnose the problems or find motive behind the response. To overcome these difficulties, marketing researchers have adapted psychoanalysis. Instead of approaching the respondents with a fixed list of questions, the interviewer is given the freedom to talk openly about the subject. The interviewer is given only general instructions about the type of information desired. The purpose of the interview is clear, but the response to the question is open ended.

iii) Structured and Indirect Interview: The structured and indirect interview has become a technique of unbiased research because the biases of the interviewer and of the interpreter are avoided. It has advantages over all the structured interviews and probes of the respondents. Instead of direct interviews, the respondents are asked the questions indirectly. It is supported on the ground that the respondents' knowledge, perception and memory are conditioned by their attitudes. When the direct question fails to get an answer, the interviewer can depend upon indirect questions. Greater knowledge reflects the strength and direction of the attitude of the respondents. When the respondents do know the answers to the questions, they guess them according to their attitude.

iv) Unstructured and Indirect Interview: The unstructured and indirect interview is very well-known as a 'projective technique. In this technique, all individuals in describing a situation interpret the situation to a degree. Various projective techniques are used, but the most common methods are word association, sentence completion and story telling.

2) Telephone Interview: The telephone interview is used when the information to be collected is limited.

The telephone interview is used -in' lieu of personal interviews. It is most frequently used when the information has to be collected quickly and inexpensively. However, it is not as versatile as personal interview -as it is difficult to handle over the telephone information needed probes. The telephone interview is suitable for inquiring about information just released or telecast by radio or television. The respondents may be asked whether they watch the particular programme regularly. What are their views about the program The indirect and unstructured questions are not suitable for the telephone interview.

3) Mail Interview: The mail interview places a great deal of importance on the construction of the questionnaire, because there is no interviewer in mail surveys to ask questions and record answers. It cannot be used to conduct an unstructured study. Personal and telephone interviews are more flexible in the sense that they can be stopped or altered at any point whereas the researcher has no control on the interview once the questionnaire is mailed. The mailing questionnaire is accompanied with a covering letter instructing the respondent how to complete the questionnaire and return the questionnaire to the researcher. The respondents complete the questionnaire at their own leisure and mail the replies to the researcher. This kind of interyiew requires that the questionnaire has to be even more carefully compiled, structure and pre-tested than the personal interview questionnaire.

4).Self-Administered Interview: The self-administered and mail survey methods have one thing in common.They differ from the other survey methods discussed in that no interviewer - human or computer - is involved. The major disadvantage of the self-administered questionnaire approach is that no one is present to explain things to the respondent and clarify responses to open-end questions.

5)Panel Interview:A panel interview may be composed of either individuals or corporate units. It is a convenient method of obtaining information about the continuing behavior of a group or-panel of respondents. The very nature of the panel interview is that the group comprising the panel-member is interviewed on the same or similar topics at regular intervals over a reasonable period of time. Since the data are obtained for a fixed panel or group over a successive period, the basis is provided for determining trends and changes over a length of time. The panel interview is not greatly different from setting up any other type of sampling operation.

6) Electronic Interview: Electronic interview could be conducted by

i) Fax: Surveys through fax have also increased in past decade. Distributing and receiving results via facsimile machines is much faster than mail. Despite improved technology the quality of print reproduction by fax is

not as good as is available in mail surveys. the much greater incidence of fax machines in,business compared to homes is a reason why this form of survey delivery is best utilized in business to business research,

ii) Internet Surveys: can be e-mail or web based approach. E-mail surveys are simple to compose and send but are limited to simple text (flat text format), allow for limited visual presentations (no photo or visual based stimuli) and interactive capabilities and cannot permit complex skip patterns. Web surveys are in HTML format 'and offer much more flexibility to the researcher, providing opportunity for presentation of complex audio and video stimuli such as animation, photos, video clips. .

Advantages of Interviewing

1) Means of Securing Detailed Information: The greatest value of this method is the depth and detail of information that can be secured. When used with a well-conceived schedule, an interview can obtain a great deal of information. It far exceeds mail survey in amount and quality of data that can be secured.

2) Encourages Inputs by Interviewer: The interviewer can do more to improve the percentage of responses and the quality of information received than other method. He can note the conditions of the interview situation, and adopt appropriate approaches to overcome such problems as the respondent's unwillingness, incorrect understanding of question, suspicion, etc.

3) Assists in Availing Supplementary Information: The interviewer can gather other supplemental information like economic level, living conditions, etc., through observation of the respondent's environment. .

4) Incorporates the Use of Devices: The interviewer can use special scoring devices, visual materials and like

in order to improve the quality of interviewing.

5) Cross Checking of Accuracy: The accuracy and dependability of the answers given by the respondent can be checked by observation and probing.

6) Flexible Exercise: Interview is flexible and adaptable to individual situations. Even more control can be exercised over the interview situation.

Limitations of Interviewing

1) Expensive: Its greatest drawback is that it is costly, both in money and time.

2) Subject to Bias and Personal Traits: The interview results are often adversely affected by interviewer's mode of asking questions and interactions, and incorrect recording and also are the respondent's faulty perception, faulty memory, inability to articulate etc.

3) Ineffective in Some areas: Certain types of personal and financial information may be refused in face-to face interviews. Such information might be supplied more willingly on mail questionnaires, especially if they are to be unsigned.

4) Recording Complexities: Interview poses the problem of recording information obtained from the respondents. No foolproof system is available. Note taking is invariably distracting to both the respondent and the interviewer and affects the thread of the conversation.

5) Demands Skilled Interviewers:Interview calls for highly skilled interviewers. The availability of such persons is limited and the training of interviewers is often a long and costly process.

6) Subjective: Interviewer's bias, i.e., it can stress on one object and neglect others.

7) Difficulty in Analysis:There are problems in interpretation and analysis because of distorted and subjective information

Questionnaire Method

The questionnaire is a list of questions to be asked from the respondents. It also contains a suitable space where se answers can be recorded.

The term questionnaire usually refers to a self-administered process where by the respondent himself reads the question and records his answers without the assistance of an interviewer. This is a narrow defination

questionnaire.

A questionnaire is a method of obtaining specific information about a defined problem so that the data, after analysis and interpretation, results in a better appreciation of the problem. A questionnaire farm, which has to be completed by an interviewer, is often referred'as schedule.

The success of collecting data either through the questionnaire method or through the schedule method depends urgely an the proper design of the questionnaire. This is a specialized jab and requires high degree of skill, experience, through knowledge of the research topic, ability to frame questions and a great deal of patience. There are no hard and fast rules in designing the 'questionnaire.

Types of Questionnaire

It is possible to classify questionnaires studies on a variety of bases. Three such bases, which are of importance,are

1)The degree to which the questionnaire is formalized or structured;

2)The disguise or lack of disguise of the objectives of the questionnaire;

3)The communication method used.

Questionnaires can be constructed so that the objective is clear to the respondent (none disguised); .or they can re constructed so as to disguise the objective, Using these two bases of classifications, four types of studies can be distinguished as below:

Structured, Non Disguised Questionnaire: Most questionnaire studies made in marketing research are of the first type- they are structured and are nat disguised. If the sales manager for a musical instrument company wants to find out how many and what type of people play various types of instruments, a formal list of questions may be set up that asks directly about the ownership and playing of various instruments. Each of a selected group of persons is then asked this set of questions in the given sequence. Answers are frequently limited to a list of alternatives, which is stated .or implied. Several questions taken from an actual survey of this type are given below,

Structured, non-disguised studies can be handled by telephone, mail, or personal interview. They are subject to the three limitations of the questionnaire -method-respondents may be unable to furnish the information desired, they may be unwilling to furnish it, or the questioning process may tend to stimulate incorrect or misleading answers:

2) Non-structured, Non-disguised Questionnaire: More than anything else, marketers want to know why people buy or do not buy their products. Direct questions dealing with motives rarely elicit useful answers. As pointed out above, most people do not have a clear idea why they make specific marketing decisions. Direct questions do not measure the relative importance of the various types of reasons, and many individuals will not report motives that might be considered base or socially unacceptable.

To overcome these difficulties, researchers have developed depth interviews and focus-group interviews Instead of approaching respondents with a fixed list of questions, the interviewer attempts to get respondents to talk freely about the subject of interest.

3) Non-structured, Disguised Questionnaire: Many people are either unwilling or unable to give accurate reports as to their own attitudes and motivations. Thus, even focus groups (nonstructured, nondisguised questioning) probably give biased results. To overcome this difficulty, clinical psychologists have developed disguised methods of gathering such data. Disguised methods are designed so that the respondents do not know what the objective of the study is. Such disguised methods may also be non- structured. Projective techniques are an example of this type.

The theory of projective techniques is that all individuals, in describing a situation, interpret that situation to a degree. The description they give is.a mixture of their own attitudes, beliefs, and motivations.

Various projective techniques are used, but the most common are word association, sentence completion. and story telling.

4) Structured, Disguised Questionnaire: Questioning of the structured, disguised type has the advantages of disguise that were pointed out above-primarily that respondents do not know what is being measured and, hence, are not biased in their answers. The advantages of structure lie in the reduction of interviewer and interpreter bias, in quicker and less costly interviewing, and in easier tabulation of results .

Some structured, disguised tests of attitudes are based on the theory that individuals;' knowledge, perception, and memory are conditioned by their attitudes.

Designing of Questionnaire

Questionnaire construction is still much more of an art than a science. Most of what is known about making questionnaires is the result of general experience. Neither a basic theory nor even a fully systematized approach to the problem has been developed.

Questionnaire construction is discussed in nine steps. These steps may vary in importance in individual projects, but each step must receive attention in each case. The nine steps are:

1) Determine What Information is Wanted:Questionnaires are prepared to meet research objectives and to motivate the respondents to cooperate with the survey. Therefore a specific statement of the information required for research purposes is prepared and put in operation to motivate the respondents. The specific characteristics of the information are decided upon for the proposed analysis and objectives.

2) Determine the Type of Questionnaire to Use: After deciding the information required for the research, the next step is to· decide the method of using the questionnaire or administering the questionnaire. The questionnaire can be used by personal interview, mail, telephone or all of them. The choice among these alternatives is largely determined by the type of information to be obtained and by the type of respondents from whom it is to be obtained. It is necessary to decide on the type of questionnaire at this point since the questions. asked, the way in which they are asked, and the sequence in which they are .asked will all be influenced by this decision. The influence of the type of questionnaire on these factors will be brought out in the discussion.

3) Determine the Content of Individual Questions: Once the needed information is specified the method of communication is decided, researchers are ready to begin formulating the questionnaire. A first problem is to decide what to include in individual questions.

4) Determine the Type of Question to Use: Once the content of individual questions is decided, researchers are ready to begin forming the actual questions. Before they can work on the wording of each question, they must decide on the type of question to use. Part of this decision is whether to use disguised or non disguised, structured or unstructured questioning. The main types of questions from least structured to most structured are:

i) Open-Ended Questions: A type of question that requires participants to respond in his/her own words without being restricted to pre-defined response choices is known as an open-ended question. They are also called infinite response or un-saturated type questions.

Open-ended questions are useful when the respondent is able to provide a narrative answer, when the researcher is uncertain what answers are needed or wants to conduct exploratory research. Such questions can be sub-divided into three sub-types:

a) Free Response: Free-response questions typically fluctuate in the degree of freedom they give to

the interviewee. '

b) . Probing: Probing open-ended questions are those where the actual open-ended questions are reached a

. '. little later in the process. '

c) Projective: A vague question or stimulus used by the researcher to project a person's attitudes from

, 'the responses is known as a projective open-ended question.

ii) Close-Ended Questions: Questions, which restrict the interviewee's answers to pre-defined re,sponse

-options, are called close-ended' questions. Close-ended questions give respondents a finite set of specified responses to choose from. Such questions are deemed appropriate when the respondent has a specific answer to give (e.g., gender), when the researcher has a pre-defined set of answers in mind, when detailed narrative information is not needed or when there is a finite number. of ways to answer a question, These q'uestions are common in survey researches.Four major structures exist for close-ended

questions. They are . . ,

a) Binary: These are also known as dichotomous questions as they permit only two possible answers.

. The respondent has to choose one of the two permissible answers.

b) Ranking Questions:These questions require the participant to rank the response options listed on a continuum basis in order of preference. Ranking questions are used to get information that reveals participants' attitudes and opinions. These questions list several alternatives that might influence an individual's decision-making. The participant assigns a rank to each option listed as per the scale mentioned. Consider the following example:

c) Multiple-Choice Questions: These questions cover all significant degrees of response. The

. respondent has to select an option that best describes their feelings.

d) Checklist Questions:These 'are questions where the participant has the freedom to choose one or more of the response' options available. This is different from multiple choice questions in that it gives freedom to the respondents to choose one or more of the options available.

5)Deciding'' on Wording of Questions: In the preceding discussion of question content and types of questions, much has been said on question wording. A number of other important ideas however should be considered. Unfortunately, these ideas are more rules of thumb that have been developed form experience than they are underlying concept.

i) Define the issue

ii) Should question be subjective or objective iii) Positive or negative statement

iv) ,Use simple wordsv) Avoid ambiguous questions

vi) Avoid leading questions

Decide on Question Sequence: Once the wording of the individual questions has been determined, it is necessary to set them' up in some order. The sequence can influence the results obtained. A questionnaire has three major sections:

i) Basic Information .

ii) Classification Information

iii) Identification Information

7) Decide on Length of Questionnaire: How long the questionnaire/ schedule would be depends upon:

i) What the researcher wants to know and how many items are necessary so that the data will be credible;

ii) On the type of study (since self-administered questionnaires may be shorter than face-to-face interviews;

iii) On the time which the researcher has available for the study;

iv) On the time the respondents can and will take; and

v) On researcher's resources.

For obtaining necessary and adequate data and credible answers, it is necessary that the length of the questionnaire should be given importance, i.e., it should be reasonably long. It is equally important that time for filling up questionnaires or responding to interview schedule is generally limited to 30-40 minutes in comparison to face-to-face interview which can continue for 45-60 minutes. Another consideration is the respondents. How long can they be available? Will they take interest in answering questions seriously? Young people may be available for less time than the middle-aged and the old people.

8) Decide on Layout and Reproduction: The physical layout and ;eproduction of the questionnaire influence the success of the interview. While planning the layout and reproduction, three important points are considered. They are:

i) Accepting of the Questionnaire: The physical appearance of the questionnaire influences the interests and attitude of the respondents. If the questionnaire is prepared on rough paper, typed unimpressively and designed poorly it may not attract the respondents to read and answer the questions. On the other hand, a questionnairetyped or printed on good quality paper may attract the respondents to read it. The respondents may be requested not to disclose their identities. The researchers, sometimes, to avoid any bias, may avoid the use of their company's name.

ii) Ease to Control: The questionnaire should be numbered serially to make it possible to control the questionnaire in the operation. It will make it easy to edit and tabulate the answers. All questions must be accounted and evaluated properly. Numbered questions are easy to follow and simple to operate throughout the survey time, and analyze thereafter.

iii) Ease of Handling: The reproduction of a questionnaire may 'influence the fieldwork lind analysis. It is essential that a large number of questions must not be put in a short space. If the questionnaire is crowded, it makes a bad appearance. This may cause errors in collection of data and tabulation as it is hard to read the answers. Too large a questionnaire cannot be handled properly. Questions should be laid out and reproduced in an easy way for the field worker to follow the sequence.

9) Check Questions: Once the first draft of the questionnaire has been completed, and before it is actually pre-tested, it is a good idea to get one (or more) expert's opinion of the questionnaire. A petson who is expert in research methodology can help to catch methodological weaknesses in the instrument, such as faulty scales, inadequate instructions, etc.' A person who is familiar with the topic of the questionnaire can help in assessing the face validity of the questions. Do they make sense; are they easy to understand, do they ask what they are supposed to asking?

10) Pretest: Before the questionnaire is ready for the field, it needs to be pre-tested under field conditions. No researcher can prepare a questionnaire so good that improvements cannot be discovered in field test. Researchers have reported pre-testing, changing, and pre-testing again for as many as 25 times before they were satisfied with some questionnaires. One pretest is as much, however, as most questionnaires get Pretests are best done by personal interview, even if the survey is to be handled by 'mail or telephone. Interviewers can note respondent reactions and attitudes which cannot otherwise be obtained. After any pertinent changes in the questionnaire have been made, another pretest can be run by mail or telephone if those methods are to be used in the survey. This latter pretest should uncover any weakness peculiar to the method of communication.

Revision and Final Draft: After each significant revision of the questionnaire, another pretest should be run..When the last pretest suggests no new revisions, the researcher is ready to print the actual questionnaires to be used in the survey. -

Qualities of a Good Questionnaire

Since The value of the results obtained from the investigation depends largely on the adequacy and appropriate of the questionnaire, the following points should be borne in mind:

Questionnair should be Brief: A large number of questions will scare away respondents. All efforts should be made to reduce the number of questions to a minimum. Irrelevant questions should be eliminated. Every question included in the questionnaire must be relevant to the problem under investigation.

Simple, Clear 'and Unambiguous Questions: The questions should be clear, unambiguous and precise. They should be unmistakable in meaning to people of varying standards of intelligence. They should be capable of being answered in only a limited number of ways. Complicated and long-worded questions irritate the informants and result in careless replies. No technical or pompous words .should be used. The language should be very simple so that informants can easily understand.

Nature of Questions: There are four types of questions, viz.,

i) Simple Alternative Questions: Such questions can be answered in 'yes' or 'no' or 'right' or 'wrong'.

The questions which can be answered clearly in 'yes' or 'no' are the best. For example, a question,

''whether you have a car" can only be answered in 'yes' or 'no'.. i

ii) Multiple Choice Questions: Such questions may be answered in a number of ways. The answers should be

printed in the questionnaire itself, and the informantshould be requested to mark against anyone of them.

iii) Specific Information Questions: Such questions solicit specific information like, - What is your age?

iv) Open Questions: Open question is one which leaves the door open to any answer. Such questions are to be answered by the informants in their own words. Such questions solicit informants' views on a particular problem.

Questions should be such that do not require-long answers. They are not expected to write an essay for you.. -

4)Use of Proper Words in the Questions: Questions should be framed with right words. The right word in

the right place will ensure the validity of answers. Words used should be such that their meanings are clear to all informants. .

5) Questions should be Such as the Answers of which are Known to Informants: The general body of informants should be in a position to answer the questions.

6) Questions Capable of Objective Answers: Questions should be capable of objective answers. Avoid questions of opinion.

'7) Should not Affect Pride or Sentiment: Questions affecting pride and sentiments of the people should not be asked. Due regard should be paid to their religious and political belief. Questions asking about private affairs should not be asked. Unduly inquisitive or offending questions should be avoided. According to Professor, Secrist, "If difficult and unfamiliar question or questions which in any way incite distrust or suspicion are asked, answers are likely to be either incomplete, brief, non-committal, general or purposely evasive."

8) Some Kind of Questions should be Avoided: Some type of questions should be avoided because their correct answers will never be got. Debatable questions should also be not asked.

9) Sequence of Questions: The arrangement or sequence of the questions is also important. According to W.M. Harper, "The questionnaire should be designed so that the questions fall into a logical sequence. This will enable the respondent to understand its purpose, and as a result the quality of his answers may be improved." Order of the questions should be such as to facilitate the answering of each question in turn.

Questions shouldi involve a logical flow of thought in the mind of informant.

10) Instructions for Filling in Questionnaire: Precise and definite instructions of filling in the questionnaire should be given. It is better to include the instruction in the body of the questionnaire than to give them as footnotes or put them altogether on the other side of the page. Instructions too should not be too lengthy.

11) Setting of Questionnaire: Some care should be taken in the actual setting out of the questionnaire. It should be made to look as attractive as possible. Plenty of space should be given for answers. A well-set questionnaire will be likely to impress the 'recipient and generally increase the rate of response.

12) To Test Accuracy:The questionnaire should include certain corroborative questions, to act as a check on false or inaccurate answers.

Advantages of Questionnaire Method

1) Economical: Questionnaires are less expensive than other methods. Even the staff required is not much as either the researcher himself may mail or one or two investigators may be appointed for hand-distributing the questionnaires. Giving salary and TAIDA to the investigators and the research officers increases the cost of the survey. In questionnaire (besides the cost of printing) the researcher has only to spend money on postage for sending the questionnaires and stamped envelopes for getting back the filled-in questionnaires or on follow-up letters.The mailed questionnaires thus cost less., .

2) Time Saving: Since the respondents may be geographically dispersed and sample size may be very large, the time required for getting back the questionnaires may be little greater but usually less than that for face-to-face interviews. Thus, since all questionnaires are sent simultaneously and most of the replies are received in 10-15 days, schedules take months to complete. In simple terms, questionnaires produce quick results.

3) Accessibility to Diverse Respondents: When the respondents are separated geographically, they can be reached by correspondence which saves travel cost. .

4) Free from Bias: Since the interviewer is not physically present at interviewee's place, he cannot influence his answers, either by prompting or by giving his own opinion or ,by misreading the question.

5) Greater Anonymity:The absence of the interviewer assures anonymity which enables respondent to express free opinions and answers even to socially undesirable questions. The absence of the interviewer assures privacy to the respondents because of which they willingly' give details of all events ann incidents they would have not revealed otherwise,

6) Respondent's Convenience: The respondent can fill-in the question-naire leisurely at his convenience. He is not forced to complete all questions at one time. Since he fills up the questionnaire in spare time, he can answer easy questions first and take time for difficult questions. ' ,\

7) Standardized Wordings:Each respondent is exposed to same words and therefore there is little difference in understanding questions. The comparison of answers is thus facilitated. . ,

8) No Variation: Questionnaires are a stable, consistent and uniform measure, without variation.

Disadvantages of Questionnaire Method

1) Unwillingness of Respondent to Provide Information: Most interviews are obtained at the sufferance of the respondent. The respondent answers, the telephone to be greeted by an interviewer 'witli a list of questions. The interviewer is unknown to the respondent, and the subject of the proposed interview may be of little or no interest. The interviewer counts on the natural politeness and good nature of most people to gain their cooperation. But in some cases potential respondents will refuse to take the time to be interviewed or will refuse to answer some specific questions.

2) Inability of Respondent to Provide Information: Despite a willingness to cooperate, many pe~ons are unable to give accurate information on questions which the marketing interviewer would like to ask. Most products are bought without any eonscious array of reasons for and against. Questions on such motivations are, therefore, apt not to obtain complete information. In other cases, respondents cannot furnish information because they are unable to remember the facts desired or because they have never known the facts.

3) Influence of Questioning Process: A third major limitation of the questionnaire methodis the effect of the questioning process on the results obtained. The situation in which a person is questioned about routine actions is an artificial one at best. As a result, respondents may furnish reports quite different from the facts.

i)Questionnaire can be administered to respondents who have considerable amount of education.

ii) Success and effectiveness mainly depends on the co-operation of the respondent.

iii)In many situations researcher is not in a position to observe the gestures/expressions of the respondent.

iv) Unintelligent answers or misinterpretation of any question by the respondent cannot be corrected.

v)Non-response rate is very high.

Precautions in Preparation of Questionnaire

Since the value of the results obtained from the investigation depends largely on the adequacy and appropriate of the questionnaire, the following points should be borne in mind:

1)Questionnaire should be Brief: A large number of questions will scare away respondents. All efforts auld be made to reduce the number of questions to a minimum. Irrelevant questions should be eliminated .ev.ery question included in the questionnaire must be relevant to the problem under investigation.

2)Simple, Clear and Unambiguous Questions: The questions should be clear, unambiguous and precise. They should be unmistakable in meaning to people of varying standards of intelligence. They should be capable of being answered in only a limited number of ways. Complicated. and long-worded questions irritate the informants and result in careless replies. No technical or pompous words should be used. The language should be very simple so that informants can easily understand. .

Nature of Questions: There are four types of questions, viz.,

i)Simple Alternative Questions: Such questions can be answered in 'yes' or 'no' or 'right' or 'wrong'.

The questions which can be answered clearly in 'yes' or 'no' are the best. For example, a question, "whether you have a car" can only be answered in 'yes' or 'no'.

ii) Multiple Choice Questions: Such questions may be answered in a number of ways. The answers should be printed in the questionnaire itself and the informant should be requested to mark against anyone of them.

iii) Specific Informatin Questions: Such questions solicit specific information like, - What is your age?

iv) Qpen- Questions: Open question is one which leaves the door open to any answer. Such questions are to be' answered by the informants in their own words. Such questions solicit informants' views on a particular problem. Questions should be such that do not require long answers. They are not expected to write an essay for you.

4)Use of Proper Words in the Questions: Questions should be framed with right words. The right word in the right place will ensure the validity of answers. Words used should be such that their meanings are clear to all informants.

5)Questions should be Such as the Answers of which are Known to Informants: The general body of informants should be in a position to answer the questions.

6)Questions Capable of Objective Answers: Questions should be capable of objective answers. Avoid questions of opinion.

7)Should not Affect Pride or Sentiment: Questions affecting pride and sentiments of the people should not be asked. Due regard should be paid to their religious and political belief. Questions asking about private affairs should not be asked. Unduly inquisitive or offending questions should be avoided. If difficult and unfamiliar question or

questions which in any way incite distrust or suspicion are asked, answers are likely to be either incomplete, brief, non-committal, general or purposely evasive. .

8)Some Kind of Questions should be Avoided: Some type of questions should be avoided because their correct answers will never be got. Debatable questions should also be not asked.

9)Sequence of the Questions: The arrangement or sequence of the questions is also important. The.questionnaire should be designed so that the questions fall into a logical sequence 'this will enable the respondent to understand its purpose, and as a result the quality of his answers may be improved. Order of the questions should be such as to facilitate the answering of each question in turn.Questions should involve a logical flow of thought in the mind of informant.

10) Instructions for Filling in the Questionnaire: Precise and definite instructions of filling in questionnaire should be given. It is better to include the instruction in the body of the questionnaire than give them as footnotes or put them altogether on the other side of the page. Instructions too should not h too lengthy.

11) Setting of the Questionnaire: Some care should be taken in the actual setting out of the questionnaire. should be made to look as attractive as possible. Plenty of space should be given for answers. A well-s questionnaire will be likely to impress the recipient and generally increase the rate of response.

12) To Test the Accuracy: The questionnaire should include certain corroborative questions, to act as a check on false or inaccurate answers.

Schedule: Schedule is a device in social research, which is most frequently used in collecting field

data especially where the survey method "is employed. It is used in indirect interview. It contains questions and' blank tables, which are to be' filled in by the investigators themselves after getting information from

the respondents. Outwardly schedule and questionnaire appear to be the same but there is some difference between the two. Schedule is used in direct interview and direct observation and is filled in by the research work himself.

According to Goode and Hatt,"Schedule is that name usually applied to a set of questions which are asked and filled in by an interviewer in a face-to-face situation with another person".

In short, it can be said that schedule is a type of proforma, which is divided into various essential headings and sub-headings according to the nature of the problem under study. In it various questionnaire induced in serial, number' so that field workers may personally ask questions to the respondents in order to collect required information.

Types of Schedule'

1) Enquiry Schedules: It is used for collecting general information or for collecting information related to census.

Field workers move from house to house, ask questions to the informants and fill the schedules by themselves. Such schedules are used mostly for knowing income, expenditure, literacy, indebtedness, occupation, family structure types of dwellings,place of residence,etc. .

2) Observation Schedule: Such schedules are used for the purpose of observation. It contains specific topics upon which the observer has to concentrate and the nature of information that he has to record. These schedules make the observation more pointed and accurate by pointing clearly what is to be observed and how is it to be recorded. '

3) Rating Schedules: Rating schedules have been mostly used in psychological research. They are used in those cases when the attitude or opinion is to be measured. Various ranks or scales are constructed and used for this purpose.

4) Documentary Schedules: Documentary schedules generally help in collecting data through secondary sources. They are used for recording data from written documents like autobiography, case history, diary, or official records maintained by the government.

5) Interview Schedules: These days such schedules are most frequently used for interview on-personal level.

These are primarily used in formal interviews. They contain standard questions that the interviewers have to ask and blank tables that he has to fill up: Accordingly interviewer asks questions from the respondents as per these schedules. Generally interview schedule becomes essential to collect information from illiterate persons. ,

Preparation of Schedule

The following procedures are adopted while framing the schedule:

1) Defining the Problem: The problem under study is first of all defined and divided into different parts. The determination of these parts will depend upon clear understanding of the problem under study and the different aspects of the problem to be studied.

2) Framing the Questionnaire: The next step is the framing of actual questions, which involves deciding the form and ,wording of the question. Full care should be taken to see that question convey the exact meaning and are easily followed by the respondents. Further care should be taken to see that respondents become willing to supply the required informatioriwithout any hesitation. When information cannot be secured by direct question, indirect questions may be asked.

Sequential Order of Questions: The third step involves the arrangement of questions. When the questions have been given definite form, the next problem is to arrange them in proper order so that accurate response is achieved and errors are avoided. '

Pilot Survey: In the last stage when the schedule becomes ready it is tested on a sample population to find out its shortcomings, if any. This is known as pilot survey.

The aims of pilot survey are to test,

i) The clarity of its wordings,

ii) The relevance of a given number of questions,

iii) The size of the schedule,

iv) The systematic order of the questions,

v) The validity of the contents, and to test its operational feature.

Advantages of Schedule Method

Higher Response: In the schedule, since a'research worker is present and he can explain and persuade the respondent, response rate is high. In case of any mistake in the schedule, the researcher can rectify it.

Saving of Time: While filling the schedule, the researcher may use abbreviation or short forms for answers, he may also generate a template. Al these steps help in saving off time in data collection.

Personal Contact: In the schedule method there is a personal contact between the respondent and the field worker. the behavior and character of respondent obviously facilitates the research work.

Human Touch: Sometimes reading something does not impress as much as when the same is heard or spoken by experts as they are able to lay the right emphasis. This greatly improves the response.

Deeper Probe: Through this method it is possible to probe deeper into the personality, living conditions, values, etc., of the respondents.

Defects in Sampling are Detected: If there are some defects in schedule during sampling it easily come to the notice and can be rectified by the researcher,

Removal of Doubts: Presence of enumerator removes the doubts in the minds of respondent on the one hand and 'avoid from the respondent artificial replies owing to fear of cross checking on the other hand

8)Human Elements make the Study more, Reliable and Dependable: The presence of human elements makes the situation more attractive and inte,resting which helps in making interview useful and reliable.

Limitations of the Schedule Method

1) Costly and Time-Consuming: This method is costly and time consuming due to its basic requirement of interviewing the respondents. This becomes a serious limitation when respondents are not found in a particular region but are scattered over a wide area.

2) Need of Trained Field Workers: The schedule method requires involvement of well-trained and experienced field workers. This involves great cost and sometimes workers are not easily available forcing engagement of inexperienced hands, which defeats the purpose trained of research.

3) Adverse Effect of Personal Presence: Sometimes personal presence of enumerator becomes an inhibiting factor. Many people despite certain facts knowing cannot say them in the presence of others., '

4) Organizational Difficulties: If the field of research is dispersed, it becomes difficult to organize it.

Getting trained manpower, assigning them duties and then administrating the research is a very difficult task.

Other Methods:

There are a number of methods for collection of data which is described as below;

1)Warranty Cards: Warranty cards are usually postal Sized cards, which are used by dealers of consumer durables to collect information regarding their products. The information sought is printed in the form of questions on the 'warranty cards' which is placed inside the package along with the product with a request to the consumer to fill in the card and post It back to the dealer.

2)Distributor or Store Audits:Distributor or store audits are performed by distributors as well as manufacturers through their sales men at regular intervals. Distributors get the retail stores audited through salesmen and use such information to estimate market size, market share, seasonal purchasing pattern and so on. The data are obtained in such audits not by questioning but by observation.

3)Pantry Audits: Pantry audit technique is used to estimate consumption of the basket of goods at the consumer level. In this type of audit, the investigator collects an inventory of types, quantities and prices of commodities consumed. Thus in pantry audit data are recorded from the examination of consumer's pantry.

4)Panels/ Consumer Panels: This form of data collection method is nowadays increasingly used for syndicated research. A panel is a group of study units (households, retail stores, organizations) that exist over time and from which data is collected on a regular-interval of time. For example; members of a consumer panel might maintain purchase diaries in which consumers record every purchase in a particular product class. Measurement of this nature provides longitudinal data and permits analysis of changes in behavior and/or attitudes.

All panels are virtually sponsored by some commercial houses and maintained by some marketing research agency in the form of syndicated research services. . '

Apart from studying the trends in the market, a panel, can also examine the changes in the market due to manipulation of many marketing mix variables. However, in order to study such dynamic behavior of panel members, the researcher would-need to adopt proper control on the experiment.

5)Use of Mechanical Devices: The use of mechanical devices has been widely made to collect information by way of indirect means. Eye camera, Pupilometric camera, Psycho-galvanometer, Motion picture camera and Audiometer are the principal devices so far developed and commonly used by modern big business houses, mostly in the developed 'World for the purpose of collecting the required information.

6)Projective Techniques: Projective techniques (or what are sometimes called as indirect interviewing techniques) for the collection of data have been developed by psychologist to use projections of respondents for inferring about underlying motives, urges, or intentions which are such' that the respondent either resists to reveal them oris unable to, figure out himself. In projective techniques the respondent in

supplying information tends unconsciously to project his own attitudes or feelings on the subject under study. Projective techniques play an important role in motivational researcher or in attitude surveys.

7)Depth Interview: when an interview is held without the aid of a structured questionnaire, the interviewer has freedom in conducting it in the manner he desires. Such interviews are not subject to a well-defined and . rigid procedure and are known as informal interviews. They are more appropriate in case of 'sensitive' issues, which may require more probing.

When a researcher is interested in in-depth investigation of perceptions, attitudes or motivations of the respondents, a formal or structured interview will not be suitable. For this purpose, an unstructured interview, which is more flexible, is used. On account of this flexibility, such interviews enable the interviewer to bring out "the affective and value-laden aspects" of the respondent's answers. Such interviews are helpful in understanding the beliefs, feelings and attitudes of respondents in their personal and social contexts.

In depth interviewing, a procedure similar to that used by a psychiatrist, is followed. A person trained in the techniques of probing conducts such an interview. He does not have a formal questionnaire with him. He asks such questions as are appropriate and in an order developed during the interview. He keenly observes and records subtle reactions of the respondent. The questions which centres around the product or problem involved are largely indirect.

8) Content Analysis:' Content analysis consists of analyzing the content of documentary materials such as books, magazines, newspapers and the contents of all.other verbal materials, which can be either spoken or printed. '

Q) Difference between Parametric and nonparametric test.

Definitions

If you’ve ever discussed an analysis plan with a statistician, you’ve probably heard the term “nonparametric” but may not have understood what it means. Parametric and nonparametric are two broad classifications of statistical procedures.

“A precise and universally acceptable definition of the term ‘nonparametric’ is not presently available. The viewpoint adopted in this handbook is that a statistical procedure is of a nonparametric type if it has properties which are satisfied to a reasonable approximation when some assumptions that are at least of a moderately general nature hold.”

That definition is not helpful in the least, but it underscores the fact that it is difficult to specifically define the term “nonparametric.” It is generally easier to list examples of each type of procedure (parametric and nonparametric) than to define the terms themselves. For most practical purposes, however, one might define nonparametric statistical procedures as a class of statistical procedures that do not rely on assumptions about the shape or form of the probability distribution from which the data were drawn.

The short explanation

Several fundamental statistical concepts are helpful prerequisite knowledge for fully understanding the terms “parametric” and “nonparametric.” These statistical fundamentals include random variables, probability distributions, parameters, population, sample, sampling distributions and the Central Limit Theorem. I cannot explain these topics in a few paragraphs, as they would usually comprise two or three chapters in a statistics textbook. Thus, I will limit my explanation to a few helpful (I hope) links among terms.

The field of statistics exists because it is usually impossible to collect data from all individuals of interest (population). Our only solution is to collect data from a subset (sample) of the individuals of interest, but our real desire is to know the “truth” about the population. Quantities such as means, standard deviations and proportions are all important values and are called “parameters” when we are talking about a population.

Since we usually cannot get data from the whole population, we cannot know the valuesof the parameters for that population. We can, however, calculate estimates of these quantities for our sample. When they are calculated from sample data, these quantities are called “statistics.” A statistic estimates a parameter. Parametric statistical procedures rely on assumptions about the shape of the distribution

(i.e., assume a normal distribution) in the underlying population and about the form or parameters (i.e., means and standard deviations) of the assumed distribution. Nonparametric statistical procedures rely on no or few assumptions about the shape or parameters of the population distribution from which the sample was drawn.

Q) Explain the Multivariate analysis

Multivariate analysis consists of a collection of methods that can be used when severalmeasurements are made on each individual or object in one or more samples. We will refer to the measurements as variables and to the individuals or objects as units (research units, sampling units, or experimental units) or observations. In practice,multivariate data sets are common, although they are not always analyzed as such.But the exclusive use of univariate procedures with such data is no longer excusable,

given the availability of multivariate techniques and inexpensive computing powerto carry them out.Historically, the bulk of applications of multivariate techniques have been in the behavioral and biological sciences. However, interest in multivariate methods has now spread to numerous other fields of investigation. For example, I have collaborated on multivariate problems with researchers in education, chemistry, physics, geology, engineering, law, business, literature, religion, public broadcasting, nursing, mining, linguistics, biology, psychology, and many other fields. Table 1.1 shows some examples of multivariate observations.The reader will notice that in some cases all the variables are measured in the same scale (see 1 and 2 in Table 1.1). In other cases, measurements are in different scales (see 3 in Table 1.1). In a few techniques, such as profile analysis (Sections 5.9 and 6.8), the variables must be commensurate, that is, similar in scale of measurement; however, most multivariate methods do not require this.Ordinarily the variables are measured simultaneously on each sampling unit. Typically, these variables are correlated. If this were not so, there would be little use for many of the techniques of multivariate analysis. We need to untangle the overlapping information provided by correlated variables and peer beneath the surface to see the underlying structure. Thus the goal of many multivariate approaches is simplifica- tion. We seek to express what is going on in terms of a reduced set of dimensions. Such multivariate techniques are exploratory; they essentially generate hypotheses rather than test them.On the other hand, if our goal is a formal hypothesis test, we need a technique that will (1) allow several variables to be tested and still preserve the significance level and (2) do this for any intercorrelation structure of the variables. Many such tests are available.

As the two preceding paragraphs imply, multivariate analysis is concerned generally with two areas, descriptive and inferential statistics. In the descriptive realm, we often obtain optimal linear combinations of variables. The optimality criterion varies from one technique to another, depending on the goal in each case. Although linear combinations may seem too simple to reveal the underlying structure, we use them for two obvious reasons: (1) they have mathematical tractability (linear approximations are used throughout all science for the same reason) and (2) they often perform well in practice. These linear functions may also be useful as a follow-up to inferential procedures. When we have a statistically significant test result that compares several groups, for example, we can find the linear combination (or combinations) of variables that led to rejection of the hypothesis. Then the contribution of each variable to these linear combinations is of interest.In the inferential area, many multivariate techniques are extensions of univariate procedures. In such cases, we review the univariate procedure before presenting the analogous multivariate approach.Multivariate inference is especially useful in curbing the researcher’s natural tendencyto read too much into the data. Total control is provided for experimentwise error rate; that is, no matter how many variables are tested simultaneously, the value of a (the significance level) remains at the level set by the

researcher. Some authors warn against applying the common multivariate techniques to data for which the measurement scale is not interval or ratio. It has been found, however, that many multivariate techniques give reliable results when applied to ordinal data.

For many years the applications lagged behind the theory because the computations were beyond the power of the available desktop calculators. However, with modern computers, virtually any analysis one desires, no matter how many variables or observations are involved, can be quickly and easily carried out. Perhaps it is not premature to say that multivariate analysis has come of age.

1.2 PREREQUISITESThe mathematical prerequisite for reading this book is matrix algebra. Calculus is not used [with a brief exception in equation (4.29)]. But the basic tools of matrix algebra are essential, and the presentation in Chapter 2 is intended to be sufficiently complete so that the reader with no previous experience can master matrix manipulation up to the level required in this book.The statistical prerequisites are basic familiarity with the normal distribution, t -tests, confidence intervals, multiple regression, and analysis of variance. These techniques are reviewed as each is extended to the analogous multivariate procedure.This is a multivariate methods text. Most of the results are given without proof. In a few cases proofs are provided, but the major emphasis is on heuristic explanations. Our goal is an intuitive grasp of multivariate analysis, in the same mode as other statistical methods courses. Some problems are algebraic in nature, but the majority involve data sets to be analyzed.1.3 OBJECTIVESI have formulated three objectives that I hope this book will achieve for the reader.These objectives are based on long experience teaching a course in multivariate methods, consulting on multivariate problems with researchers in many fields, and guiding statistics graduate students as they consulted with similar clients.

The first objective is to gain a thorough understanding of the details of various multivariate techniques, their purposes, their assumptions, their limitations, and so on. Many of these techniques are related; yet they differ in some essential ways. We emphasize these similarities and differences.

The second objective is to be able to select one or more appropriate techniques for a given multivariate data set. Recognizing the essential nature of a multivariate data set is the first step in a meaningful analysis. We introduce basic types of multivariate data in Section 1.4.

The third objective is to be able to interpret the results of a computer analysis of a multivariate data set. Reading the manual for a particular program package is not enough to make an intelligent appraisal of the output. Achievement of the firs to bjective and practice on data sets in the text should help achieve the third objective.

1.4 BASIC TYPES OF DATA AND ANALYSISWe will list four basic types of (continuous) multivariate data and then briefly describe some possible analyses. Some writers would consider this an oversimpli- fication and might prefer elaborate tree diagrams of data structure. However, many data sets can fit into one of these categories, and the simplicity of this structure makes it easier to remember. The four basic data types are as follows:1. A single sample with several variables measured on each sampling unit (subject or object);2. A single sample with two sets of variables measured on each unit;3. Two samples with several variables measured on each unit;4. Three or more samples with several variables measured on each unit.

Each data type has extensions, and various combinations of the four are possible.A few examples of analyses for each case are as follows:1. A single sample with several variables measured on each sampling unit:(a) Test the hypothesis that the means of the variables have specified values.(b) Test the hypothesis that the variables are uncorrelated and have a common variance.

(c) Find a small set of linear combinations of the original variables that summarizes most of the variation in the data (principal components).(d) Express the original variables as linear functions of a smaller set of underlying variables that account for the original variables and their intercorrelations (factor analysis).2. A single sample with two sets of variables measured on each unit:(a) Determine the number, the size, and the nature of relationships between the two sets of variables (canonical correlation). For example, you may wish to relate a set of interest variables to a set of achievement variables.How much overall correlation is there between these two sets?(b) Find a model to predict one set of variables from the other set (multivariate multiple regression).3. Two samples with several variables measured on each unit:(a) Compare the means of the variables across the two samples (Hotelling’s T 2 -test).(b) Find a linear combination of the variables that best separates the two sam- ples (discriminant analysis).(c) Find a function of the variables that accurately allocates the units into the two groups (classification analysis).4. Three or more samples with several variables measured on each unit:(a) Compare the means of the variables across the groups (multivariate analysis of variance).(b) Extension of 3(b) to more than two groups.(c) Extension of 3(c) to more than two groups.

Q) Define Multiple RegressionMultiple regression is a flexible method of data analysis that may be appropriate whenever a quantitative variable (the dependent or criterion variable) is to be examined in relationship to any other factors (expressed as independent or predictor variables). Relationships may be nonlinear, independent variables may be quantitative or qualitative, and one can examine the effects of a single variable or multiple variables with or without the effects of other variables taken into account (Cohen, Cohen, West, & Aiken, 2003).

Multiple Regression Models and Significance TestsMany practical questions involve the relationship between a dependent or criterion variable of interest (call it Y) and a set of k independent variables or potential predictor variables (call them X1, X2, X3,..., Xk), where the scores on all variables are measured for N cases. For example, you might be interested in predicting performance on a job (Y) using information on years of experience (X1), performance in a training program (X2), and performance on an aptitude test (X3). A multiple regression equation for predicting Y can be expressed a follows:

(1)To apply the equation, each Xj score for an individual case is multiplied by the corresponding Bj value, the products are added together, and the constant A is added to the sum. The result is Y, the predicted Y value for the case.

For a given set of data, the values for A and the B js are determined mathematically to minimize the sum of squared deviations between predicted Y and the actual Y scores. Calculations are quite complex, and best performed with the help of a computer, although simple cases with only one or two predictors can be solved by hand with special formulas.

The correlation between Y and the actual Y value is also called the multiple correlation coefficient, Ry.12...k, or simply R. Thus, R provides a measure of how well Y can be predicted from the set of X scores. The following formula can be used to test the null hypothesis that in the population there is no linear relationship between Y and prediction based on the set of k X variables from N cases:

(2) .

For the statistical test to be accurate, a set of assumptions must be satisfied. The key assumptions are that cases are sampled randomly and independently from the population, and that the deviations of Y values from the predicted Y values are normally distributed with equal variance for all predicted values of Y.

Alternatively, the independent variables can be expressed in terms of standardized scores where Z1 is the z score of variable X1, etc. The regression equation then simplifies to:

(3) ZY = ß1Z1 + ß2Z2 + ß3Z3 .The value of the multiple correlation R and the test for statistical significance of R are the same for standardized and raw score formulations.