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1. Mention difference between Parametric Tests and Non Parametric Tests. Parametric and non-parametric statistical tests differ in the type of data they're used to analyze. Parametric tests make many assumptions, the most significant of which is that the data are normally distributed. Non-parametric tests make fewer assumptions and deal with data that are not normally distributed. Parametric tests generally have higher statistical power. Parametric tests make the assumption from prior knowledge that the data are normally distributed. Various tests can be performed to determine whether or not this is a valid assumption. If the data aren't normally distributed, they may be transformed in various ways so that parametric tests can still be used. Alternatively, non-parametric analyses can be used. Non-parametric tests make no assumptions about the distribution of data. Parametric tests make the assumption that the data are measured on an interval scale, so that the interval between data points is meaningful. Height in inches or weight in pounds are interval data. By contrast, non-parametric tests make no assumptions about the scale of the data. Parametric tests employ parameters that can estimated with a data set that is normally distributed. The mean, variance, standard deviation and skewedness are examples. These parameters are used to make inferences in parametric tests. By contrast, non-parametric tests do not make use of these statistical parameters. In general, the statistical power is lower in non-parametric tests than in their parametric counterparts. Statistical power refers to the probability that the statistical test will reject the null hypothesis when the null hypothesis is in fact false, and thus should be rejected. In other words, power refers to the likelihood that the test will lead to the correct inference about the population. 2. Write a short note on Factor Analysis. A method of quantitative multivariate analysis with the goal of representing the interrelationships among a set of continuously measured variables (usually represented by their inter-correlations) by a number of underlying, linearly

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1. Mention difference between Parametric Tests and Non Parametric Tests.

Parametric and non-parametric statistical tests differ in the type of data they're used to analyze. Parametric tests make many assumptions, the most significant of which is that the data are normally distributed. Non-parametric tests make fewer assumptions and deal with data that are not normally distributed. Parametric tests generally have higher statistical power.

Parametric tests make the assumption from prior knowledge that the data are normally distributed. Various tests can be performed to determine whether or not this is a valid assumption. If the data aren't normally distributed, they may be transformed in various ways so that parametric tests can still be used. Alternatively, non-parametric analyses can be used. Non-parametric tests make no assumptions about the distribution of data.

Parametric tests make the assumption that the data are measured on an interval scale, so that the interval between data points is meaningful. Height in inches or weight in pounds are interval data. By contrast, non-parametric tests make no assumptions about the scale of the data.

Parametric tests employ parameters that can estimated with a data set that is normally distributed. The mean, variance, standard deviation and skewedness are examples. These parameters are used to make inferences in parametric tests. By contrast, non-parametric tests do not make use of these statistical parameters.

In general, the statistical power is lower in non-parametric tests than in their parametric counterparts. Statistical power refers to the probability that the statistical test will reject the null hypothesis when the null hypothesis is in fact false, and thus should be rejected. In other words, power refers to the likelihood that the test will lead to the correct inference about the population.

2. Write a short note on Factor Analysis.

A method of quantitative multivariate analysis with the goal of representing the interrelationships among a set of continuously measured variables (usually represented by their inter-correlations) by a number of underlying, linearly independent reference variables called factors. Although the term factor analysis has come to represent a family of analysis methods, the two most commonly used approaches are the full component model, in which the entire variance of the variables (represented by unities inserted in the principal diagonal of the correlation matrix) is analyzed, and the common factor model, in which the proportion of the variance that is accounted for by the common factors (represented by communality estimates inserted in the principal diagonal) is analyzed.The method was developed in England around the turn of the century and was first applied to the study of the structure of intellectual abilities. Since then it has been used in many disciplines, from agriculture to zoology, in which the underlying structure of multiple variables and their representation in that structure are of interest. Another application of factor analysis is to represent parsimoniously the variables in the set on which the observations are made by a smaller number of underlying reference variables or factors.

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3. Write a short note on Research Design

The next step after stating the management problem, research purpose, and research hypotheses and questions, is to formulate a research design. The starting point for there search design is, in fact, the research questions and hypotheses that have been so carefully developed. In essence, the research design answers the question: How are we going to get answers to these research questions and test these hypotheses? The research design is a plan of action indicating the specific steps that are necessary to provide answers to those questions, test the hypotheses, and thereby achieve the research purpose that helps choose among the decision alternatives to solve the management problem or capitalize on the market opportunity

According to David J. Luck and Ronald S. Rubin,

"A research design is the determination and statement of the general research approach or strategy adopted/or the particular project. It is the heart of planning. If the design adheres to the research objective, it will ensure that the client's needs will be served."

4. Explain the steps in Research Process.

STEPS

IN PLANNING THE RESEARCH DESIGN:

There are four broad steps involved in planning the research design as explained below:

(1) Determining work involved in the project:

(2) Estimating costs involved

3) Preparing time schedule:

4) Verifying result

5. Differentiate between

i) Pure Research and Applied- Research can either be applied (or action) research orfundamental (to basic or pure) research. Applied research aims at finding a solution for animmediate problem facing a society or an industrial/business organisation, whereas fundamentalresearch is mainly concerned with generalisations and with the formulation of a theory.“Gathering knowledge for knowledge’s sake is termed ‘pure’ or ‘basic’ research.”4 Researchconcerning some natural phenomenon or relating to pure mathematics are examples offundamental research. Similarly, research studies, concerning human behaviour carried onwith a view to make generalisations about human behaviour, are also examples offundamental research, but research aimed at certain conclusions (say, a solution) facing aconcrete social or business problem is an example of applied research. Research to identify

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social, economic or political trends that may affect a particular institution or the copy research(research to find out whether certain communications will be read and understood) or themarketing research or evaluation research are examples of applied research. Thus, thecentral aim of applied research is to discover a solution for some pressing practical problem,whereas basic research is directed towards finding information that has a broad base ofapplications and thus, adds to the already existing organized body of scientific knowledge.

ii) Questionnaire and Schedule

The important points of difference are as under:

1. The questionnaire is generally sent through mail to informants to be answered as specifiedin a covering letter, but otherwise without further assistance from the sender. The schedule is generally filled out by the research worker or the enumerator, who can interpret questionswhen necessary.2. To collect data through questionnaire is relatively cheap and economical since we have tospend money only in preparing the questionnaire and in mailing the same to respondents.Here no field staff required. To collect data through schedules is relatively more expensivesince considerable amount of money has to be spent in appointing enumerators and inimporting training to them. Money is also spent in preparing schedules.3. Non-response is usually high in case of questionnaire as many people do not respond andmany return the questionnaire without answering all questions. Bias due to non-responseoften remains indeterminate. As against this, non-response is generally very low in case ofschedules because these are filled by enumerators who are able to get answers to allquestions. But there remains the danger of interviewer bias and cheating.4. In case of questionnaire, it is not always clear as to who replies, but in case of schedule theidentity of respondent is known.5. The questionnaire method is likely to be very slow since many respondents do not returnthe questionnaire in time despite several reminders, but in case of schedules the informationis collected well in time as they are filled in by enumerators.6. Personal contact is generally not possible in case of the questionnaire method asquestionnaires are sent to respondents by post who also in turn return the same by post.But in case of schedules direct personal contact is established with respondents.7. Questionnaire method can be used only when respondents are literate and cooperative, butin case of schedules the information can be gathered even when the respondents happen tobe illiterate.8. Wider and more representative distribution of sample is possible under the questionnairemethod, but in respect of schedules there usually remains the difficulty in sendingenumerators over a relatively wider area.9. Risk of collecting incomplete and wrong information is relatively more under the questionnairemethod, particularly when people are unable to understand questions properly. But in caseof schedules, the information collected is generally complete and accurate as enumeratorscan remove the difficulties, if any, faced by respondents in correctly understanding thequestions. As a result, the information collected through schedules is relatively more accuratethan that obtained through questionnaires.10. The success of questionnaire method lies more on the quality of the questionnaire itself, butin the case of schedules much depends upon the honesty and competence of enumerators.11. In order to attract the attention of respondents, the physical appearance of questionnairemust be quite attractive, but this may not be so in case of schedules as they are to be filledin by enumerators and not by respondents.12. Along with schedules, observation method can also be used but such a thing is not possiblewhile collecting data through questionnaires.

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iii) Descriptive and Analytical Research.

Descriptive research includes surveys and fact-finding enquiriesof different kinds. The major purpose of descriptive research is description of the state ofaffairs 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 main characteristicof this method is that the researcher has no control over the variables; he can only reportwhat has happened or what is happening. Most ex post facto research projects are usedfor descriptive studies in which the researcher seeks to measure such items as, for example,frequency of shopping, preferences of people, or similar data. Ex post facto studies alsoinclude attempts by researchers to discover causes even when they cannot control thevariables. The methods of research utilized in descriptive research are survey methods ofall kinds, including comparative and correlational methods. In analytical research, on theother hand, the researcher has to use facts or information already available, and analyzethese to make a critical evaluation of the material.

iv) References and Bibliography.

1.Bibliography is listing all the materials that have been consulted while writing an essay or a book. References, on the other hand, are those that have been referenced in your article or book.2.Bibliography is not directly included in the text. References are those that are directly included in your actual text.3.Both bibliography and references are arranged alphabetically. But a Reference list can also be arranged in Numeric style

6. Describe the role of Computers in Research.

To the researcher, the use of computer to analyse complex data has made complicated researchdesigns practical. Electronic computers have by now become an indispensable part of researchstudents in the physical and behavioural sciences as well as in the humanities. The research student,in this age of computer technology, must be exposed to the methods and use of computers. A basicunderstanding of the manner in which a computer works helps a person to appreciate the utility ofthis powerful tool. Performing calculations almost at the speed of light, the computer has become one of the most usefulresearch tools in modern times. Computers are ideally suited for data analysis concerning largeresearch projects. Researchers are essentially concerned with huge storage of data, their fasterretrieval when required and processing of data with the aid of various techniques. In all these operations,computers are of great help. Their use, apart expediting the research work, has reduced humandrudgery and added to the quality of research activity.

Techniques involving trial and error process are quite frequently employed in research methodology.This involves lot of calculations and work of repetitive nature. Computer is best suited for suchtechniques, thus reducing the drudgery of researchers on the one hand and producing the final resultrapidly on the other. Thus. different scenarios are made available to researchers by computers in notime which otherwise might have taken days or even months.The storage facility which the computers provide is of immense help to a researcher for he canmake use of stored up data whenever he requires to do so.Thus, computers do facilitate the research work. Innumerable data can be processed and analyzedwith greater ease and speed. Moreover, the results obtained are generally correct and reliable. Notonly this, even the design, pictorial graphing and report are being developed with the help of computers.Hence, researchers should be given computer education and be trained in the line so that they can

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use computers for their research work.