Website Sources for research Data

Research Methods-I BSCS-SEM-VI #WaqarSeyal P a g e | 1

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[email protected] BSCS-308 IIIIII JAN-2014IIIIII PAGES-64IIIIIIII

RESEARCH

METHODS-I

BS COMMUNICATION STUDIES


OBJECTIVES

This course will give the students an insight into the basic principles of

scientific research. Students will further be sensitized with the methods,

techniques and other relevant concepts to investigate the media related

phenomena in contemporary society.

COURSE CONTENT

1. Defining Research

2. Concepts Of Research In Mass Communication

3. Steps In Research

4. Elements Of Research

Concepts

Constructs

Variables

Research question

Hypothesis

5. Measurement Levels And Scale

6. Kinds Of Scientific Research

Qualitative and Quantitative

Basic and Applied

Historical Research

Observational

Descriptive Research

Correlation Research

Experimental Research

7. Sampling And Its Techniques

8. Literature Review And Its Techniques

9. Ethics In Research

Code Cr. Hrs Semester Year

BSCS-308 3 VI 3


TABLE OF CONTENTS COURSE CONTENT .......................................................................................................................................... 2

1. DEFINING RESEARCH ........................................................................................................................ 4

2. CONCEPTS OF RESEARCH IN MASS COMMUNICATION ........................................................... 7

3. STEPS IN RESEARCH .......................................................................................................................... 7

4. ELEMENTS OF RESEARCH .............................................................................................................. 10

4.1 CONCEPTS ...................................................................................................................................... 10

4.2 CONSTRUCTS.................................................................................................................................. 11

4.3 VARIABLES ...................................................................................................................................... 12

4.4 RESEARCH QUESTION .................................................................................................................... 14

4.5 HYPOTHESIS ................................................................................................................................... 15

5. NON DIRECTIONAL HYPOTHESIS ............................................................................................. 16

6. CAUSAL HYPOTHESIS.................................................................................................................. 16

5. MEASUREMENT LEVELS AND SCALE ......................................................................................... 17

6. KINDS OF SCIENTIFIC RESEARCH ................................................................................................ 24

6.1 QUALITATIVE AND QUANTITATIVE ................................................................................................ 24

6.2 BASIC AND APPLIED ....................................................................................................................... 27

6.3 HISTORICAL RESEARCH .................................................................................................................. 29

6.4 OBSERVATIONAL ............................................................................................................................ 31

6.5 DESCRIPTIVE RESEARCH ................................................................................................................. 35

6.6 CORRELATION RESEARCH .............................................................................................................. 37

6.7 EXPERIMENTAL RESEARCH ............................................................................................................ 40

7. SAMPLING AND ITS TECHNIQUES ............................................................................................... 46

8. LITERATURE REVIEW AND ITS TECHNIQUES ........................................................................... 53

9. ETHICS IN RESEARCH ...................................................................................................................... 59

MISCELLANEOUS ..................................................................................................................................... 62


1. DEFINING RESEARCH DEFINITIONS Definitions by Dr. Robert V. Williams:

1. Thorough and systematic inquiry or investigation into a subject in order to discover facts or principles.

2. A studious inquiry or examination, especially a critical investigation . . . having as its aim the discovery of new facts and their correct interpretation, the revision of accepted conclusions,

theories, or laws in the light of new discovered facts, or the practical application of such

conclusions, theories or laws.

An attempt to discover new or collate old facts etc by the scientific study of a subject or by a

course of critical investigation. [Oxford Concise Dictionary]

Research may be defined as a collaborative activity by means of which a given phenomenon in

reality is studied in an objective manner, with a view to establishing a valid understanding of that

phenomenon.

Research involves the use of carefully prescribed methods and procedures to systematically

observe, collect, and analyze empirical data.

A systematic investigation (i.e., the gathering and analysis of information) designed to develop or contribute to generalizable knowledge.

The Advanced Learners Dictionary of Current English lays down the meaning of research as a careful investigation or inquiry specially through search for new facts in any branch of

knowledge. Redman and Mory define research as a systematized effort to gain new knowledge. According to Clifford Woody research comprises defining and redefining problems, formulating

hypothesis or suggested solutions; collecting, organising and evaluating data; making deductions

and reaching conclusions; and at last carefully testing the conclusions to determine whether they

fit the formulating hypothesis.

D. Slesinger and M. Stephenson in the Encyclopedia of Social Sciences define research as the manipulation of things, concepts or symbols for the purpose of generalising to extend, correct or

verify knowledge, whether that knowledge aids in construction of theory or in the practice of an

art.

Martyn Shuttleworth - "In the broadest sense of the word, the definition of research includes any

gathering of data, information and facts for the advancement of knowledge."

Creswell who states - "Research is a process of steps used to collect and analyze information to

increase our understanding of a topic or issue". It consists of three steps: Pose a question, collect

data to answer the question, and present an answer to the question.

The Merriam-Webster Online Dictionary : "a studious inquiry or examination; especially :

investigation or experimentation aimed at the discovery and interpretation of facts, revision of

accepted theories or laws in the light of new facts, or practical application of such new or revised

theories or laws"

Research can be defined to be search for knowledge or any systematic investigation to establish

facts.

A detailed study of a subject, especially in order to discover (new) information or reach a (new)

understanding.

New knowledge is created through research. Research is based on primary and secondary sources,

often together with original data collected via research "instruments" (surveys, interviews,

questionnaires, "focus groups," etc.) to produce new knowledge on a particular topic.

In addition to primary sources and original instruments, secondary sources are used to provide an

overview of existing published knowledge on a topic, and possible current debates about the topic.


The background provided by secondary sources provides a contextual background and establishes

how the new knowledge described in a paper differs from what is already known.

The purpose of all research is to describe and explain variance in the world. Variance is simply the

difference; that is, variation that occurs naturally in the world or change that we create as a result of a

manipulation.

All research focuses on "solving problems" at minimum, as it concerns FIN-1, answering the defined research question(s). Otherwise, research addresses the perceived "problem" of missing or

inadequate information on a particular topic.

The emphasis and methodology of research may differ between different fields and disciplines,

particularly between the Sciences and the Humanities. However, most fields share the following

concerns:

Discovering the relevant "facts" of an event, issue, procedure, or problem;

Reviewing and evaluating contrasting explanations for the topic being researched, especially

explanations which may differ from what the current research has concluded;

Reviewing the consensus (or lack of it) of the research findings among researchers;

Disseminating the findings and conclusions for critical review.

GENERAL CHARACTERISTICS OF RESEARCH

The following characteristics may be gathered from the definitions of Research

1. It gathers new knowledge or data from primary or first-hand sources. 2. It places emphasis upon the discovery of general principles. 3. It is an exact systematic and accurate investigation. 4. It uses certain valid data gathering devices. 5. It is logical and objective. 6. The researcher resists the temptation to seek only the data that support his hypotheses. 7. The researcher eliminates personal feelings and preferences. 8. It endeavours to organise data in quantitative terms. 9. Research is patient and unhurried activity. 10. The researcher is willing to follow his procedures to the conclusions that may be unpopular and

bring social disapproval.

11. Research is carefully recorded and reported. 12. Conclusions and generalisations are arrived at carefully and cautiously.

PURPOSE/ OBJECTIVES/ FUNCTIONS OF RESEARCH/ What Does

Research Do?

To gain familiarity with a phenomenon or to achieve new insights into it.

To portray accurately the characteristics of a particular individual, situation or a group.

To determine the frequency with which something occurs or with which it is associated with something else.

To test a hypothesis of a causal relationship between variables. to learn something,

to gather evidence.

Advancement of Human Knowledge Solution to a larger problem Collate and synthesize existing information Extracting new meaning to extend human knowledge of the physical, biological, or social world beyond what is already

known.


THE FUNCTIONS OF RESEARCH

The main function of research is to improve research procedures through the refinement and extension of knowledge.

The Researches should contribute to the theory and practice of study studies simultaneously. It should have the image of a helpful mechanism which can be used by researcher/research-scholar

in one way or the other, for the improvement of the process.

Exploration

A great deal of social research is conducted to explore a topic or familiarize oneself with a topic. This

typically occurs when a researcher becomes interested in a new topic or when the subject of study

itself is relatively new. Often times, exploratory research is done through the use of focus groups or

small group discussions, which are frequently used in market research.

Exploratory studies are typically done for three purposes: to satisfy the researchers curiosity and desire for better understanding, to test the feasibility of undertaking a more extensive study, and to

develop the methods to be employed in any subsequent studies.

Description

Another major purpose of social research is to describe situations and events. The researcher observes

and then describes what he or she observed. One great example of descriptive social research is the

Pakistani Census. The goal of the census is to describe accurately and precisely several characteristics

of the Pakistani population, including race/ethnicity, age, sex, household size, income, etc.

Explanation

A third major purpose of social research is to explain things. While descriptive studies attempt to

answer the what, when, where, and how, explanatory studies attempt to answer the why. For example,

reporting the crime rates of different cities is descriptive. Identifying the variables that explain why

some cities have higher crime rates than others involves explanation. Likewise, reporting the

frequency of church attendance is descriptive, but reporting why some people attend church while

others dont is explanatory.

IMPORTANCE

The main purpose and role of research is to help plan and gather information on a certain topic

before carrying it out. It helps to test and create a theory on a certain things and with the

information given, to gather and generate a topic to find out more on it.

Research inculcates scientific and inductive thinking and it promotes the development of logical

habits of thinking and organisation.

The role of research in several fields of applied economics, whether related to business or to the

economy as a whole, has greatly increased in modern times.

Research provides the basis for nearly all government policies in our economic system.

Research has its special significance in solving various operational and planning problems of

business and industry.

Research is equally important for social scientists in studying social relationships and in seeking

answers to various social problems.


2. CONCEPTS OF RESEARCH IN

MASS COMMUNICATION Media Research involves the collection of data about the various advertising media, surveying consumers on their media preferences and habits, and carrying out primary and

secondary research on effectiveness of each medium for selling particular types of products.

The Mass Communication Research (Research

of Mass Communication) is a stream that breaks in

the middle of the twentieth century with the

primary objective of analyzing the social, cultural

and psychological messages that are transmitted

by the mass media and public reactions to media

proposals in order to get the keys to drive the

behavior of the masses.

Advertising Research

Market Research

PR Research

Media Effects

Functional, Critical Research

Ratings (TRP)

Target Audience

It supports audience. It supports media & trend analysis. It does message testing It does issue monitoring, forecasting & evaluating. It often provides essential data for effectively presenting information. To formulate strategy. To gauge success. To test messages. To size up competition. To get publicity. To sway opinion.

3. STEPS IN RESEARCH STEPS IN RESEARCH PROCESS

1. IDENTIFY AND FORMULATE RESEARCH PROBLEM Articulate a research question

What exactly is being researched and why; what the relevance or importance is; what questions will

be addressed, and an overview of what conclusions will be drawn.

There are two types of research problems, viz., those which relate to states of nature and those which

relate to relationships between variables. At the very outset the researcher must single out the problem

he wants to study, i.e., he must decide the general area of interest or aspect of a subject-matter that he

would like to inquire into.


The statement of the problem is the focal point of your research. It should state what you will be

studying, whether you will do it through experimental or non-experimental investigation, and what the

purpose of your findings will be.

The first step in the process is to identify a problem or develop a research question.

It is one of the first statements made in any research paper and, as well as defining the research area,

should include a quick synopsis of how

the hypothesis was arrived at.

A quantitative experimental design uses deductive

reasoning to arrive at a testable hypothesis.

Qualitative research designs use inductive reasoning to

propose a research statement.

An anthropologist might find references to a relatively

unknown tribe in Papua New Guinea.

Through inductive reasoning, she arrives at the

research problem and asks,

How do these people live and how does their culture relate to nearby tribes?

She has found a gap in knowledge, and she seeks to fill it, using a qualitative case study, without a

hypothesis.

The Bandura Bobo Doll Experiment is a good example of using deductive reasoningto arrive at a

research problem and hypothesis.

2. REVIEWING THE LITERATURE 3. DEVELOPMENT OF WORKING HYPOTHESES

o Conceptualization and operationalization of concepts and variables

o Defining Terms

o Clarify and narrow down the Problem

Many times the initial problem identified in the first step of the process is too large or broad in scope.

In step 3 of the process, the researcher clarifies the problem and narrows the scope of the study. This

can only be done after the literature has been reviewed. The knowledge gained through the review of

literature guides the researcher in clarifying and narrowing the research project.

Terms and concepts are words or phrases used in the purpose statement of the study or the description

of the study. These items need to be specifically defined as they apply to the study. Terms or concepts

often have different definitions depending on who is reading the study. To minimize confusion about

what the terms and phrases mean, the researcher must specifically define them for the study.

4. PREPARING THE RESEARCH DESIGN

The overall design of a research project consists of its methods and procedures. Research design can

be described as Qualitative or Quantitative in approach. It is also possible to have a mixture of the

two approaches, both in overall design and in the specific methods used in the investigation.

Selltiz et al., in their classical book on research methodology, define research design in the following

manner: 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.

5. RESEARCH METHODOLOGY o Make instrumental plan o Theoretical framework


In this section the purpose and research questions or hypotheses are re-stated, and the exact nature of

what is being researched and how (population and sampling) is defined, along with what

instrumentation was used (copies of instruments should be included in Appendices). Also in this

section are details on the procedure and time frame of the research, the analysis plan, the validity and

reliability of the data used, the author's assumptions which are based on the research, and possible

limitations to these

assumptions, or other

conclusions.

Research methodology is a

way to systematically solve the

research problem. In it we

study the various steps that are

generally adopted by a

researcher in studying his

research problem along with

the logic behind them.

The plan for the study is

referred to as the

instrumentation plan. The

instrumentation plan serves as

the road map for the entire

study, specifying who will participate in the study; how, when, and where data will be collected; and

the content of the program.

6. DEFINING POPULATION AND DETERMINING SAMPLE DESIGN

The preparation of the research design, appropriate for a particular research problem, involves usually

the consideration of the following:

the means of obtaining the information;

the availability and skills of the researcher and his staff (if any);

explanation of the way in which selected means of obtaining information will be organized and

the reasoning leading to the selection;

the time available for research; and

the cost factor relating to research, i.e., the finance available for the purpose.

7. COLLECTION OF DATA o Collect, record, classify, and control data.

Once the instrumentation plan is completed, the actual study begins with the collection of data. The

collection of data is a critical step in providing the information needed to answer the research

question. Every study includes the collection of some type of datawhether it is from the literature or from subjectsto answer the research question. Data can be collected in the form of words on a survey, with a questionnaire, through observations, or from the literature.

8. ANALYZING THE DATA AND INTERPRETING THE RESULTS

The researcher finally has data to analyze so that the research question can be answered. In the

instrumentation plan, the researcher specified how the data will be analyzed. The researcher now

analyzes the data according to the plan. The results of this analysis are then reviewed and summarized

in a manner directly related to the research questions.

Significant test


To test a hypothesis, quantitative research uses significance tests to determine which hypothesis is

right. The significance test can show whether the null hypothesis is more likely correct than the

research hypothesis. Research methodology in a number of areas like social sciences depends heavily

on significance tests.

9. COMMUNICATING THE RESULTS / CONCLUSION Suggest possible application of the findings and conclusions.

A summary of the nature and application of the "new knowledge" represented in your paper. Also

included here are possible contraindications of your conclusions, along with proposed further research

based on your findings (and the possible contraindications).

Discussion of 'Limitations': This section is increasingly a part of research articles published in

academic journals. It is a separate section of the paper which describes real or potential faults with the

methodology, research material, or other factors that could have influenced the research findings.

Limitations: Limitations are shortcomings, conditions or influences that cannot be controlled by the

researcher that place restrictions on your methodology and conclusions.

10. CITE PROPERLY AND GIVE CREDIT FOR SOURCES OF IDEAS.

4. ELEMENTS OF RESEARCH

4.1 CONCEPTS What is a concept? A general notion, conception, comprehension, A thing formed in the mind,

A directly conceived or intuited object of thought

An idea of something formed by mentally combining all its characteristics or particulars

A general idea derived or inferred from specific instance or occurrence.


Concepts may be defined as the most elementary symbolic constructions by means of which people classify or categorize reality.

A concept is a notion about a natural phenomenon. For example "mass" is a concept having different

notions to different people. To a scientist mass is a term for the physical appearance of a matter but to

a social scientist mass is general public. So is the apprehension about the term "medium" to

a layman it is about the size but to a media person it is the channel and tool of communication.

Concepts are abstract symbols (words) that represent some phenomena, idea, or entity. Concepts can

be very abstract (romantic love) or they can be more concrete (income).

Concepts are important for at least two reasons:

First, they simplify the research process by combining particular characteristics, objects, or people

into more general categories.

Second, concepts simplify communication among those who have a shared understanding of them.

Researchers use concepts to organize their observations into meaningful summaries and to

transmit this information to others.

4.2 CONSTRUCTS DEFINITIONS

A construct is the combination of two concepts. A construct is deliberately and consciously invented or created for a specific scientific purpose. It is a concept or idea that may be abstract or concrete or even observable. Constructs are mental abstractions that we used to express

the ideas, people, organisations, events and/or objects/things that we are interested in.

A construct is a collection of other related behaviours that are associated in a meaningful way. A construct is a concept that has three distinct characteristics:

1. First, it is an abstract idea that is usually broken down into dimensions represented by lower level concepts.

2. Second, because of its abstraction, a construct usually cannot be observed directly. 3. Third, a construct is usually designed for some particular research purpose so that its exact

meaning relates only to the context in which it is found.

We often refer to constructs as mental abstractions because seldom are constructs directly

observable (e.g., we cannot directly observe depression, even though we may associate depression

with signs such as a person that often cries, engages in self-harm, has mood swings, and so forth).

Since constructs are very broad and abstract, conceptual clarity has become one of the cornerstones

of good research.

Constructs provide a common language and shared meaning that help us to communicate about

things clearly and precisely. Constructs need to be expressed (i.e., made explicit) in a way that is

clear, precise, and non-ambiguous.

EXAMPLES For example "Mass" is a concept, "Media" is again a concept and the "Mass Media" is a

construct which give a third meaning as a whole phrase.

For example, "intelligence" is an idea, a part of what that makes us human and is made up of lots

of smaller ideas. Intelligence is a construct based on observation of presumably intelligent and less

intelligent behaviours. For example, "intelligence" is made up of several behaviours such verbal

ability, quantitative ability, spatial ability, mechanical reasoning, inductive thinking and so forth.

The table below provides some examples of different types of constructs:

Types of constructs

Examples

Ideas Ageism, sexism, racism, self-esteem, poverty, social capital, trust, philanthropy,

morality, tolerance, air pollution, genetic engineering, marriage..


People Age, gender, ethnicity, height, obesity, energy, muscle soreness, fatigue

Organizations Financial performance, corporate social responsibility, firm survival,

organizational culture, service quality, corporate governance

Events famine, Jihad, secularism

Objects/Things Sun, hurricanes, tsunamis, trees, flowers..

4.3 VARIABLES DEFINITION

It is the changing value of quantity or quality of a thing or concept is called variable.

Concepts that represent phenomena that can take on different values, quantities, or intensities are

called variables. A variable is something that varies. A variable is a construct that is deliberately and

consciously invented or adopted for a special scientific purpose.

An event or behavior that has at least two values.

TYPES 1. INDEPENDENT VARIABLE It is the variable whose value is independent to change and normally it is denoted by "x" and is placed

horizontally on the graph with its negative values on

the opposite side if required. For example "speed" , Media exposure.

An independent variable (IV) (treatment variable, precdictor variables, input variable) is the variable

that is presumed can cause a change in the dependent variable.

Dependent variables are observed and their values presumed to depend on the effects of the

independent variables. In other words, the dependent variable is what the researcher wishes to explain.

Causes are called INDEPENDENT VARIABLES. If one variable truly causes a second, the cause is

the independent variable. Independent variables are often also called explanatory

variables or predictors.

There are two types of independent variables: Active and attribute.

a. ATTRIBUTE: level or score of the variable is brought to the experiment by the subject, usually as a natural characteristic such as sex, age, etc. An attribute variable is a variable where we do not

alter the variable during the study. For example, we might want

to study the effect of age on weight. We cannot change a

person's age, but we can study people of different ages and

weights.

b. ACTIVE: the level of the IV is manipulated by the experimenter. If the independent variable is an active variable

then we manipulate the values of the variable to study its affect

on another variable.

2. DEPENDENT VARIABLE It is the variable whose value is dependent

to change and normally it is denoted by "y" and is placed vertically on

the graph with its negative values on the opposite side if required. For example "distance",

Socialization from media etc.

Independent variables are systematically varied by the researcher.

Effects are called DEPENDENT VARIABLES. We explain what has caused dependent variables.

Dependent variables are also sometimes called outcome, output, result, response or criterion variables.

This is the variable that is affected by the independent variable.


3. INTERVENING VARIABLE/ Extraneous It is the variable that effects the relation of the independent and dependent variable. For example in `

"quality of the road" is an intervening variable.

Uncontrolled or unobserved variables that may account for variation in the Dependent Variable.

This is a variable that probably does influence the relationship between the independent and

dependent variables, but it is one that we do not control or manipulate. Extraneous variables which

influence the study in a negative manner are often called confounding variables.

4. MEDIATING VARIABLES

A mediating variable is defined as one that links between the independent and the dependent variable.

Thus, an mediating variable is part of a causal chain:

INDEPENDENT VARIABLE -------> MEDIATOR VARIABLE ------> DEPENDENT VARIABLE

Mediator variables inform us about causal sequences or chains, thus explaining the causal process of a

phenomenon.

EXAMPLE: educational level -----> occupational type -----> income level

5. Control variable:

Any variable that may affect Dependent Variable should be controlled; that is, measured and

accounted for statistically or held constant (age, gender, socioeconomic status, etc., could be control

variables)

A control variable is a variable that effects the dependent variable. When we "control a variable" we

wish to balance its effect across subjects and groups so that we can ignore it, and just study the

relationship between the independent and the dependent variables. You control for a variable by

holding it constant, e.g., keep humidity the same, and vary temperature, to study comfort levels.

CONCEPTUAL VARIABLES:

CONCEPTUAL VARIABLES are what you think the entity really is or what it means. Conceptual

variables are about abstract constructs. YOU DO NOT DISCUSS MEASUREMENT AT THIS

STAGE! Examples include "achievement motivation" or "endurance" or "second language".

OPERATIONAL VARIABLES:

On the other hand, OPERATIONAL VARIABLES (sometimes called "operational definitions")

are how you actually measure this entity, or the concrete operations, measures, or procedures that you

use to measure the concept in practice. If you use a Stanford-Binet to measure intelligence or a bar

code scan to assess the popularity of musical artists, those are operational variables.

CATEGORICAL AND CONTINUOUS VARIABLE A variable can be either a categorical variable (nominal variable) or a continuous

variable (ordinal variable).

Continuous Variable: A continuous variable has numeric values such as 1, 2, 3, 4, etc. The relative

magnitude of the values is significant (e.g., a value of 2 indicates twice the magnitude of 1). Examples

of continuous variables are blood pressure, height, weight, income, age, scores on a history test.

Categorical Variable: In the case of the variable "gender" there are only 2 values; i.e. male and

female and is called categorical or nominal variable

In the case of the variable "gender" there are only 2 values, i.e. male (1) and female (0). When

variables have only two values, they are called dichotomous variables. Variables with more than two


values are called polytomies. Examples are Religion - Islam, Christianity, Buddhism. Hinduism and

Socio-economic status - high, medium & low.

Discrete variables: Variables that usually consist of whole number units or categories and are made

up of chunks or units that are detached and distinct from one another.

Continuous variables: Variables that usually fall along a continuum and allow for fractional

amounts.

4.4 RESEARCH QUESTION A research question summarizes the key relationship between an independent and dependent variable

youll focus on in your report.

A research question proposes a relationship between two or more variables. Just as the title states, it

is structured in form of a question.

A research question is a formal statement of the goal of a study. The research question states clearly

what the study will investigate or attempt to prove. The research question is a logical statement that

progresses from what is known or believed to be true (as determined by the literature review) to that is

unknown and requires validation.

TYPES OF QUESTIONS

There are three basic types of questions that research projects can address:

1. DESCRIPTIVE. When a study is designed primarily to describe what is going on or what exists. Public opinion polls that seek only to describe the proportion of people who hold

various opinions are primarily descriptive in nature. For instance, if we want to know what

percent of the population would vote for a Democratic or a Republican in the next presidential

election, we are simply interested in describing something.

A descriptive research question seeks to identify and describe some phenomenon.

An example: What is the ethnic breakdown of patients seen in the emergency room for non-

emergency conditions.

2. RELATIONAL. When a study is designed to look at the relationships between two or more variables. A public opinion poll that compares what proportion of males and females say they

would vote for a Democratic or a Republican candidate in the next presidential election is

essentially studying the relationship between gender and voting preference.

3. CAUSAL. When a study is designed to determine whether one or more variables (e.g., a program or treatment variable) causes or affects one or more outcome variables. If we did a

public opinion poll to try to determine whether a recent political advertising campaign

changed voter preferences, we would essentially be studying whether the campaign (cause)

changed the proportion of voters who would vote Democratic or Republican (effect).

A relationship question asks if two or more phenomena are related in some systematic manner.

For example: If one increases his level of physical exercise does muscle mass also increase?

4. A differences research question asks if there are differences between groups on some phenomenon.

For example: Do patients who receive massage experience more relief from sore muscle pain than

patients who take a hot bath?


4.5 HYPOTHESIS DEFINITION

An hypothesis is a specific statement of prediction. It describes in concrete (rather than theoretical) terms what you expect will happen in your study.

A hypothesis is: A specified testable expectation about empirical reality that follows from a more general proposition; more generally, an expectation about the nature of things derived from a

theory. It is a statement of something that ought to be observed in the real world if the theory is

correct. A hypothesis represents a declarative statement, a sentence instead of a question, of the cause-

effect relationship between two or more variables.

A hypothesis is an informed and educated prediction or explanation about something.

In research, a hypothesis is a suggested explanation of a phenomenon.

A prediction regarding the outcome of a study that often involves the relationship between two

variables.

A hypothesis may describe whether there is a relationship, no relationship predicted at all, the causal direction of the relationship, the mechanics (how) of the relationship, and may even

specify the form of the relationship.

EXAMPLES

An external threat raises team cohesiveness. Children with an encyclopedia in their home will achieve higher scores on the intelligence

Test.

Fast walking will lower Galvanic Skin Response scores.

TYPES 1. NULL HYPOTHESIS The hypothesis predicting that no difference exists between the groups being compared.

A null hypothesis is a hypothesis which a researcher tries to disprove. Normally, the null hypothesis

represents the current view/explanation of an aspect of the world that the researcher wants to

challenge.

This is the conventional approach to making a prediction. It involves a statement that says there is no

relationship between two groups that the researcher compares on a certain variable. The hypothesis

may also state that there is no significant difference when different groups are compared with respect

to a particular variable. For example, "There is no difference in the academic performance of high

school students who participate in extracurricular activities and those who do not participate in such

activities" is a null hypothesis. In many cases, the purpose of the null hypothesis is to allow the

experimental results to contradict the hypothesis and prove the point that there is a definite

relationship.

In classical statistics inference testing, it is mathematically the easiest to disprove a null hypothesis,

which is sometimes written as Ho. A null hypothesis will assert that:

There is no relationship among two or more variables (EXAMPLE: the correlation between

educational level and income is zero)

Or that two or more populations or subpopulations are essentially the same (EXAMPLE: women

and men have the same average science knowledge scores.)


If your prediction specifies a direction, and the null therefore is the no difference prediction and the

prediction of the opposite direction, we call this a one-tailed hypothesis.

When your prediction does not specify a direction, we say you have a two-tailed hypothesis.

2. RESEARCH HYPOTHESIS/ ALTERNATIVE HYPOTHESIS The hypothesis that the researcher wants to support and that predicts a significant difference exists

between the groups being compared.

Research methodology involves the researcher providing an alternative hypothesis, a research

hypothesis, as an alternate way to explain the phenomenon.

If the null hypothesis is rejected, typically an alternative hypothesis (usually styled HA:) is accepted.

Usually the alternative hypothesis will assert that a relationship among two or more variables exists or

that two or more subpopulations differ in some respect. A direction to the relationship (e.g., external

threat raises team cohesion) may be specified. Directional alternative hypothesis are specified in

advance of data collection procedures.

The researcher tests the hypothesis to disprove the null hypothesis, not because he/she loves the

research hypothesis, but because it would mean coming closer to finding an answer to a specific

problem. The research hypothesis is often based on observations that evoke suspicion that the null

hypothesis is not always correct.

3. DESCRIPTIVE

Descriptive hypotheses ask a specific question regarding some phenomenon. Descriptive hypotheses

are always phrased in the form of a question regarding some aspect of the research question. Usually a

descriptive hypothesis does not include an active independent variable.

4. DIRECTIONAL HYPOTHESIS

Directional hypotheses are never phrased as a question, but always as a statement. Directional

hypotheses always express the effect of an independent on a dependent variable. When we use an

independent variable, a directional hypothesis is usually needed.

Investigator bases this hypothesis on the trends apparent from previous research on this topic.

Example: High school students who participate in extracurricular activities have a lower GPA than those who do not participate in such activities." Such hypotheses provide a definite direction to the

prediction.

5. NON DIRECTIONAL HYPOTHESIS

Certain hypothesis statements convey a relationship between the variables that the researcher

compares, but do not specify the exact nature of this relationship. This form of hypothesis is used in

studies where there is no sufficient past research on which to base a prediction.

6. CAUSAL HYPOTHESIS

Some studies involve a measurement of the degree of influence of one variable on another. In such

cases, the researcher states the hypothesis in terms of the effect of variations in a particular factor on

another factor.

ONE-TAILED HYPOTHESIS (DIRECTIONAL HYPOTHESIS): An alternative hypothesis in

which the researcher predicts the direction of the expected difference between the groups.

TWO-TAILED HYPOTHESIS (NON-DIRECTIONAL HYPOTHESIS): An alternative

hypothesis in which the researcher predicts that the groups being compared differ but does not predict

the direction of the difference.


The logic of hypothesis testing is based on these two basic principles:

The formulation of two mutually exclusive hypothesis statements that, together, exhaust all possible outcomes

The testing of these so that one is necessarily accepted and the other rejected.

ERRORS IN RESEARCH

Logically, there are two types of errors when drawing conclusions in research:

1. Type 1 error is when we accept the research hypothesis when the null hypothesis is in fact correct.

2. Type 2 error is when we reject the research hypothesis even if the null hypothesis is wrong.

THE DIFFERENCE BETWEEN RESEARCH QUESTIONS & HYPOTHESIS

HYPOTHESIS RESEARCH QUESTION Definitions A hypothesis is defined as an educated

guess.

A research question is simply the researcher

wondering about the world.

Structure Hypothesis are written as statements

preceded with the words "I predict."

As its name suggests, research questions are

always written as questions.

Before

Writing

Before writing a hypothesis, the researcher

must determine what others have

discovered about this subject.

On the other hand, a research question requires

less preparation, but focus and structure is

critical.

Writing

Conclusions

the researcher will write whether the

hypothesis was correct or incorrect,

followed by an explanation of the results.

The researcher using only a research question

will write the answer to the question, followed by

the findings of the research.

5. MEASUREMENT LEVELS AND

SCALE Measurement is the assignment of numerals to objects or events according to rules.

Level of measurement refers to the way that a variable is measured.

The level of measurement refers to the relationship among the values that are assigned to the

attributes for a variable.

In statistics and research methodology, levels of

measurement or scales of measure are types of

data that arise in the theory of scale

types developed by the psychologist Stanley Smith

Stevens.

Stevens proposed his typology in a

1946 Science article titled "On the theory of scales

of measurement". In that article, Stevens claimed

that all measurement in science was conducted

using four different types of scales that he called

"nominal," "ordinal," "interval," and "ratio,"

unifying both "qualitative" and "quantitative"

Before we can conduct a statistical analysis, we need to measure our dependent variable. Exactly how

the measurement is carried out depends on the type of variable involved in the analysis.


Although procedures for measurement differ in many ways, they can be classified using a few

fundamental categories. In a given category, all of the procedures share some properties that are

important for you to know about. The

categories are called "scale types," or just

"scales.

The level of measurement for a particular

variable is defined by the highest category

that it achieves.

It's important to recognize that there is a

hierarchy implied in the level of

measurement idea. At lower levels of

measurement, assumptions tend to be less restrictive and data analyses tend to be less sensitive. At

each level up the hierarchy, the current level includes all of the qualities of the one below it and adds

something new. In general, it is desirable to have a higher level of measurement (e.g., interval or

ratio) rather than a lower one (nominal or ordinal).

Why is Level of Measurement Important?

First, knowing the level of measurement helps you decide how to interpret the data from that variable.

Second, knowing the level of measurement helps you decide what statistical analysis is appropriate on

the values that were assigned.

Being familiar with the level of measurement of the variables in your data set is crucial because they

will help determine what statistical procedure you use. Not every statistical operation can be used

with every variable. The type of procedure used depends on the variables level of measurement.

SCALE TYPES WITH THEIR PROPERTIES ACCORDING TO STANLEY SMITH

STEVENS

Nominal scale Ordinal scale Interval scale Ratio scale

Logical/

math

operations

+

-

<

>

=

Examples: Dichotomous

and

non-

dichotomous

Variable name

(data values)

Dichotomous:

Gender

(male vs. female)

Non-dichotomous:

Nationality

(American/Chinese/etc)

Dichotomous:

Health

(healthy vs. sick),

Truth

(true vs. false),

Beauty

(beautiful vs.ugly)

Non-dichotomous:

Opinion

('completely agree'/

Date

(from 1457 BC

to AD 2013)

Latitude

(from +90 to

90)

Age

(from 0 to 99

years)


'mostly agree'/

'mostly disagree'/

'completely

disagree')

Measure of

central

tendency

Mode Median Arithmetic Mean Geometric Mean

Qualitative or

Quantitative Qualitative Qualitative Quantitative Quantitative

1. NOMINAL SCALE

The nominal type, sometimes also called the qualitative type, differentiates between items or subjects

based only on their names or (meta-)categories and other qualitative classifications they belong to.

A nominal scale, as the name implies, is simply some placing of data into categories, without any

order or structure.

The lowest level is the nominal scale. This may be thought of as the naming level.

With nominal scales, you can tell whether two cases or instances fall into the same category or into

different categories. Thus, you can sort all cases into mutually exclusive, exhaustive categories.

It refers to quality more than quantity. A nominal level of measurement is simply a matter of

distinguishing by name, e.g., 1 = male, 2 = female. They are categories or classifications.

Because the different categories (for instance, males and females) vary in quality but not quantity,

nominal variables are often called qualitative variables. An important feature of nominal variables is

that there is no hierarchy or ranking to the categories.

No data is captured that can place the measured object on any kind of scale say, for example, on a

continuum from one to ten. Coding of nominal scale data can be accomplished using numbers, letters,

labels, or any symbol that represents a category into which an object can either belong or not belong.

This classifies individuals, companies, products, brands or other entities into categories where no

order is implied.

EXAMPLES

In research activities a YES/NO scale is nominal. It has no order and there is no distance between

YES and NO.

When we ask subjects to name their marital status, they will respond with wordsnot numbersthat describe their status such as married, single, divorced, etc. Notice that nominal data do not put subjects in any particular order. There is no logical basis for saying that one category such

as single is higher or lower than any other. Examples of nominal scales include: Zodiac sign, Gender, Birth country and Religious affiliation

(or denomination), POLITICAL ORIENTATION, Language, Genre

A physical example of a nominal scale is the terms we use for colours. The underlying spectrum is

ordered but the names are nominal.

Nominal time of day: AM&PM - categories; no additional information.

STATISTICAL OPERATIONS


The nominal scale forms the basis for such analyses as Analysis of Variance (ANOVA) because those

analyses require that some category is compared to at least one other category.

cross-tabulation - with chi-square

Central tendency: The mode, i.e. the most common item, is allowed as the measure of central tendency for the nominal type. On the other hand, the median, i.e. the middle-ranked item,

makes no sense for the nominal type of data since ranking is not allowed for the nominal type.

2. ORDINAL SCALE

At this level we put subjects in order from high to low.

Ordinal scales involve the ranking of individuals, attitudes or items along the continuum of the

characteristic being scaled.

With ordinal scales, the categories themselves can be rank-ordered from highest to lowest.

Ordinal refers to order in measurement. An ordinal scale indicates direction, in addition to providing

nominal information. Low/Medium/High; or Faster/Slower are examples of ordinal levels of

measurement.

The ordinal type allows for rank order (1st, 2nd, 3rd, etc.) by which data can be sorted, but still does

not allow for relative degree of difference between them.

A researcher wishing to measure consumers' satisfaction

with their microwave ovens might ask them to specify their

feelings as either "very dissatisfied," "somewhat

dissatisfied," "somewhat satisfied," or "very satisfied." The

items in this scale are ordered, ranging from least to most satisfied.

This means the scores must be rank-ordered from highest to lowest (or vice versa) first, before you

can use any ordinal measures. Like runners in a race, we can rank scores--and the categories

themselves--from first to last, most to least, or highest to lowest.

In rank-ordered cases, we can literally rank order the finishers in a race or the students by their

grade point average (first in class, second in class, and so on down to last in class). Notice that the

intervals between cases probably are not the same (or equal).

Strongly Agree Agree Disagree or Strongly Disagree with that statement.

The simplest ordinal scale is a ranking. An ordinal scale only lets you interpret gross order and not

the relative positional distances.

When a market researcher asks you to rank 5 types of beverages from most flavourful to least

flavourful, he/she is asking you to create an ordinal scale of preference.

There is no objective distance between any two points on your subjective scale. For you the top

beverage may be far superior to the second prefered beverage but, to another respondant with the

same top and second beverage, the distance may be subjectively small.

The ordinal scale has at least one major advantage over the nominal scale. The ordinal scale contains

all of the information captured in the nominal scale but it also ranks data from lowest to highest.

Rather than simply categorize data by placing an object either into or not into a category, ordinal data

give you some idea of where data lie in relation to each other.

Unlike nominal scales, ordinal scales allow comparisons of the degree to which two subjects possess

the dependent variable. For example, our satisfaction ordering makes it meaningful to assert that one

person is more satisfied than another with their microwave ovens. Such an assertion reflects the first

person's use of a verbal label that comes later in the list than the label chosen by the second person.


On the other hand, ordinal scales fail to capture important information that will be present in the

other scales we examine. In particular, the difference between two levels of an ordinal scale cannot be

assumed to be the same as the difference between two other levels.

EXAMPLES

For example, if a researcher asked farmers to rank 5 brands of Detergent in order of preference.

For instance, an employer might rank order applicants for a job on their professional appearance.

Traditionally, we give a rank of 1 to the subject who is highest, 2 to the next highest, and so on. It

is important to note that ranks do not tell us by how much subjects differ. To measure the amount

of difference among subjects, we use the next levels of measurement.

For example, social class is an ordinal variable because we can say that a person in the category

"upper class" has a higher class position than a person in a middle class category, which again is higher than "lower class."

RANK: 1st place, 2nd place, ... last place

LEVEL OF AGREEMENT: No, Maybe, Yes

POLITICAL ORIENTATION: Left, Center, Right

the order of finish (e.g., class rank or a horse race)

collapses of numeric data into categories with unequal widths or intervals (e.g., collapsing

years of education into degree level).

Ordinal time of day - indicates direction or order of occurrence; spacing between is uneven

STATISTICAL OPERATIONS Median and mode

Rank order correlation

Non-parametric analysis of variance.

Modeling techniques can also be used with ordinal data.

Boolean operations possible

Central tendency: The median, i.e. middle-ranked, item is allowed as the measure of central

tendency; however, the mean (or average) as the measure of central tendency is not allowed.

The mode is allowed.

3. INTERVAL SCALE

The interval scale indicates the distance one object is from another.

Unlike the nominal and ordinal scales, you can make relative distance measurements among objects

using the interval scale.

In interval measurement, the distance between the attributes, or categories, does have meaning.

Interval scales are numerical scales in which intervals have the same interpretation throughout.

The interval type allows for the degree of difference between items, but not the ratio between them.

Interval scales provide information about order, and also possess equal intervals. The standard survey

rating scale is an interval scale.

It is an interval scale because it is assumed to have equidistant points between each of the scale

elements. This means that we can interpret differences in the distance along the scale. We contrast this

to an ordinal scale where we can only talk about differences in order, not differences in the degree of

order.


It is only with an interval scaled data that researchers can justify the use of the arithmetic mean as the

measure of average. The interval or cardinal scale has equal units of measurement, thus making it

possible to interpret not only the order of scale scores but also the distance between them. However, it

must be recognized that the zero point on an interval scale is arbitrary and is not a true zero.

It is possible to add or subtract a constant to all of the scale values without affecting the form of the

scale but one cannot multiply or divide the values.

Interval scales are not perfect, however. In particular, they do not have a true zero point even if one of

the scaled values happens to carry the name "zero." The Fahrenheit scale illustrates the issue. Zero

degrees Fahrenheit does not represent the complete absence of temperature (the absence of any

molecular kinetic energy).

EXAMPLES

For example, when we measure temperature (in Fahrenheit), the distance from 30-40 is same as

distance from 70-80. The interval between values is interpretable. Because of this, it makes sense

to compute an average of an interval variable, where it doesn't make sense to do so for ordinal

scales. But note that in interval measurement ratios don't make any sense - 80 degrees is not twice

as hot as 40 degrees (although the attribute value is twice as large). Scores obtained using objective tests such as multiple-choice tests of achievement.

POLITICAL ORIENTATION: Score on standardized scale of political orientation

Interval time of day - equal intervals; analog (12-hr.) clock, difference between 1 and 2 pm is same as

difference between 11 and 12 am Interval scales may be either numeric or semantic.

STATISTICCAL OPERATIONS

Central tendency and statistical dispersion: The mode, median, and arithmetic mean are

allowed to measure central tendency of interval variables, while measures of statistical

dispersion include range and standard deviation.

Mean and standard deviation

Correlation r

Regression

Analysis of variance

Factor analysis

Plus a whole range of advanced multivariate and modeling techniques

4. RATIO SCALE

The scale that contains the richest information about an object is ratio scaling. In addition to all the

properties of nominal, ordinal, and interval variables, ratio variables also have a fixed/non-arbitrary

zero point (a point where none of the quality being measured exists).

Ratio levels have an absolute zero that is meaningful (i.e. no numbers exist below zero). That is, you

can construct a meaningful ratio, or fraction, with a ratio variable.

Using a ratio scale permits comparisons such as being twice as high, or one-half as much.

The ratio scale of measurement is the most informative scale. It is an interval scale with the additional

property that its zero position indicates the absence of the quantity being measured. You can think of


a ratio scale as the three earlier scales rolled up in one. Like a nominal scale, it provides a name or

category for each object (the numbers serve as labels). Like an ordinal scale, the objects are ordered

(in terms of the ordering of the numbers). Like an interval scale, the same difference at two places on

the scale has the same meaning. And in addition, the same ratio at two places on the scale also carries

the same meaning.

The highest level of measurement is a ratio scale. This has the properties of an interval scale together

with a fixed origin or zero point. Examples of variables which are ratio scaled include weights,

lengths and times. Ratio scales permit the researcher to compare both differences in scores and the

relative magnitude of scores. For instance the difference between 5 and 10 minutes is the same as that

between 10 and 15 minutes, and 10 minutes is twice as long as 5 minutes.

EXAMPLES

For example, the number of clients in past six months. Why? Because you can have zero clients and

because it is meaningful to say that "...we had twice as many clients in the past six months as we did

in the previous six months."

The Fahrenheit scale for temperature has an arbitrary zero point and is therefore not a ratio scale.

However, zero on the Kelvin scale is absolute zero. This makes the Kelvin scale a ratio scale. For

example, if one temperature is twice as high as another as measured on the Kelvin scale, then it has

twice the kinetic energy of the other temperature.

Another example of a ratio scale is the amount of money you have in your pocket right now (25

cents, 55 cents, etc.). Money is measured on a ratio scale because, in addition to having the properties

of an interval scale, it has a true zero point: if you have zero money, this implies the absence of

money.

Examples include mass, length, duration, plane angle, energy and electric charge.

RULER: inches or centimeters

INCOME: money earned last year

GPA: grade point average

YEARS of work experience

NUMBER of children

STATISTICAL OPERATIONS Central tendency and statistical dispersion: The geometric mean and the harmonic mean are allowed

to measure the central tendency, in addition to the mode, median, and arithmetic mean. The range and

the coefficient of variation are allowed to measure statistical dispersion. All statistical measures are

allowed because all necessary mathematical operations are defined for the ratio scale.


6. KINDS OF SCIENTIFIC RESEARCH

6.1 QUALITATIVE AND QUANTITATIVE QUANTITATIVE RESEARCH

Quantitative research, involving the counting and measuring of communication events, is often

equated with scientific empiricism. The approach yields a body of numerical data, which the

researchers analyze statistically. Any of the materials including measurement techniques, sampling

methods, and statistical tests are geared toward quantitative research. Importantly, quantitative

analysis may be conducted in naturalistic or laboratory research settings and may be applied to vast

array of communication phenomena including mass media, organizational communication, &

interpersonal interaction. The approach is distinguished, only by its use of numerical data as a means

of understanding the nature of human communication. Quantitative research is concerned with how

often a variable is present and generally uses numbers to communicate this amount. In quantitative

research, reality is objective; which exist apart from researchers and can be seen by all. It believes all

human beings are basically similar and looks for general categories to summarize their behavior or

feelings.

The quantitative in quantitative research contains the word quantitysomething that can be counted. So quantitative research includes any research methods that produce hard numbers which

can be turned into statistics. Census is an example of large-scale quantitative research in action.

Quantitative research methods, including surveys and controlled experiments.

Market researchers conduct surveys to find out demographic information about their customers.

Quantitative research aim to measure the quantity or amount and compares it with past records and

tries to project for future period. In social sciences, quantitative research refers to the systematic empirical investigation of quantitative properties and phenomena and their relationships. The objective of qualitative research is to develop and employ mathematical models, theories or

hypothesis pertaining to phenomena. The process of measurement is central to quantitative research

because it provides fundamental connection between empirical observation and mathematical

expression of quantitative relationships. Statistics is the most widely used branch of mathematics in

quantitative research. Statistical methods are used extensively with in fields such as economics and

commerce. Quantitative research involving the use of structured questions, where the response

options have been Pre-determined and large number of respondents is involved.

There are a number of core characteristics to quantitative dissertations:

They typically attempt to build on and/or test theories, whether adopting an original approach or

an approach based on some kind of replication or extension.

They answer quantitative research questions and/or research (or null) hypotheses.

They are mainly underpinned by positivist or post-positivist research paradigms.

They draw on one of four broad quantitative research

designs (i.e., descriptive, experimental, quasi-experimental or relationship-based research

designs).

They try to use probability sampling techniques, with the goal of making generalisations from

the sample being studied to a wider population, although often end up applying non-probability

sampling techniques.

They use research methods that generate quantitative data (e.g., data sets, laboratory-based

methods, questionnaires/surveys, structured interviews, structured observation, etc.).

They draw heavily on statistical analysis techniques to examine the data collected,

whether descriptive or inferential in nature.


They assess the quality of their findings in terms of their reliability, internal and external

validity, and construct validity.

They report their findings using statements, data, tables and graphs that address each research

question and/or hypothesis.

They make conclusions in line with the findings, research questions and/or hypotheses,

and theories discussed in order to test and/or expand on existing theories, or providing insight

for future theories.

QUALITATIVE RESEARCH

Although statistical analysis is prominent in communication research, much contemporary inquiry is

qualitative. Often equated with humanistic studies, qualitative research rejects numerical measures in

favor of narrative data, meaning that qualitative data" appear in words rather than in numbers.

Examples of qualitative data may include transcripts of naturalistic conversation, communication

documents such as public speeches and media artifacts like printed editorials and videotapes of

television of programs. Qualitative analysis involves the critical analysis and synthesis of narrative

information to derive verbal rather than statistical conclusions about the contents and functions of

human talk.

Chadwick, Bahr, &Albrecht, (1984) defined it as Qualitative research refers to several methods of data collection which include focus groups, field observations, in-depth interviews, and case studies.

Although there are substantial differences among these techniques, all involve what some writers refer

to as 'getting close to the data

While quantitative research can tell you when, where, and how often things happen, qualitative

research looks at the why and how. Qualitative research produces observations, notes, and descriptions of behavior and motivation. Research methods in this category include:

Interviews: either a series of structured questions, or allowing a subject to narrate their experience

Focus groups: soliciting observations from groups of people who share a similar attribute (for example, a group of women over 40) to give opinions on a topic

Reviews: Combing through scholarly literature or other published writings to determine attitudes towards a subject

Observation: researchers watch people on their daily routine and make notes or recordings documenting their behavior

Qualitative research presents non-qualitative type of analysis. Qualitative research is collecting,

analyzing and interpreting data by observing what people do and say. Qualitative research research

refers to the meanings, definitions, characteristics, symbols, metaphors, and description of things.

Qualitative research is much more subjective and uses very different methods of collecting

information,mainly individual, indepth interviews and focus groups. The nature of this type of

research is exploratory and open ended. Small number of people are interviewed in depth and or a

relatively small number of focus groups are conducted. Qualitative research can be further classified

in the following type:

I. Phenomenology:-a form of research in which the researcher attempts to understand how one or more individuals experience a phenomenon. Eg:-we might interview 20 victims of bhopal

tragedy.

II. Ethnography:- this type of research focuses on describing the culture of a group of people. A culture is the shared attributes, values, norms, practices, language, and material things of a

group of people. Eg:-the researcher might decide to go and live with the tribal in Andaman

island and study the culture and the educational practices. III. Case study:-is a form of qualitative research that is focused on providing a detailed account of

one or more cases


IV. Grounded theory:- it is an inductive type of research, based or grounded in the observations of data from which it was developed; it uses a variety of data sources,

including quantitative data, review of records, interviews, observation and surveys V.

Historical research:-it allows one to discuss past and present events in the context of the

present condition, and allows one to reflect and provide possible answers to current

issues and problems.

There are a number of broad characteristics to qualitative dissertations:

They follow an emergent design, meaning that the research process, and sometimes even

the qualitative research questions that you tackle, often evolve during the dissertation process.

They use theory in a variety of ways - sometimes drawing on theory to help the research

process; on other occasions, using theory to develop new theoretical insights; sometimes both -

but the goal is infrequently to test a particular theory from the outset.

They can be underpinned by one of a number of research

paradigms (e.g., interpretivism, constructivism, critical theory, amongst many other research

paradigms).

They follow research designs that heavily influence the choices you make throughout the

research process, as well as the analysis and discussion of 'findings' (i.e., such research designs

differ considerably depending on the route that is being followed, whether

an autoethnography, case study research, ethnography, grounded theory, narrative

research,phenomenological research, etc.).

They try to use theoretical sampling - a group of non-probability sampling techniques - with

the goal of studying cases (i.e., people or organisations) that are most appropriate to answering

their research questions.

They study people in-the-field (i.e., in natural settings), often using multiple research methods,

each of which generate qualitative data (e.g., unstructured interviews, focus

groups,participant observation, etc.).

They interpret the qualitative data through the eyes and biases of the researcher, going back-

and-forth through the data (i.e., an inductive process) to identify themes or abstractions that

build a holistic/gestalt picture of what is being studied.

They assess the quality of their findings in terms of

their dependability, confirmability, conformability and transferability.

They present (and discuss) their findings through personal accounts, case studies, narratives,

and other means that identify themes or abstracts, processes, observations andcontradictions,

which help to address their research questions.

They discuss the theoretical insights arising from the findings in light of the research questions,

from which tentative conclusions are made.

COMBINING RESEARCH METHODS

Naturally, you can use a mix of research methods to help gather comprehensive evidence or give a

more complete picture of what it is youre studying.

QUALITATIVE VERSUS QUANTITATIVE RESEARCH

Criteria Qualitative Research Quantitative Research

Purpose To understand & interpret

social interactions.

To test hypotheses, look at cause &

effect, & make predictions.

Group Studied Smaller & not randomly selected. Larger & randomly selected.

Variables Study of the whole, not variables. Specific variables studied

Type of Data Collected Words, images, or objects. Numbers and statistics.


Form of Data Collected Qualitative data such as open- ended

responses, interviews, participant

observations, field notes, &

reflections.

Quantitative data based on

precise measurements using

structured & validated data-

collection instruments.

Type of Data Analysis Identify patterns, features, themes. Identify statistical relationships.

Objectivity and Subjectivity Subjectivity is expected. Objectivity is critical.

Role of Researcher Researcher & their biases may be

known to participants in the study, &

participant characteristics may be

known to the researcher.

Researcher & their biases are not

known to participants in the study,

& participant characteristics are

deliberately hidden from the

researcher (double blind studies).

Results Particular or specialized findings

that is less generalizable.

Generalizable findings that can be

applied to other populations.

Scientific Method Exploratory or bottomup: the researcher generates a new

hypothesis and theory from the data

collected.

Confirmatory or top-down: the

researcher tests the hypothesis and

theory with the data.

View of Human Behavior Dynamic, situational, social, &

personal.

Regular & predictable.

Most Common

Research Objectives

Explore, discover, & construct. Describe, explain, & predict.

Focus Wide-angle lens; examines the

breadth & depth of phenomena.

Narrow-angle lens; tests a

specific hypotheses.

Nature of Observation Study behavior in a natural

environment.

Study behavior under

controlled conditions;

isolate causal effects.

Nature of Reality Multiple realities; subjective. Single reality; objective.

Final Report

Narrative report with contextual

description & direct quotations

from research participants.

Statistical report with

correlations, comparisons of

means, & statistical

significance of findings.

Setting for data gathering

Natural environment of research

Participants

Office, agency, or via mail or

Internet

6.2 BASIC AND APPLIED

Basic research looks at causes, effects, and the nature of things Applied research tries to find answers and solutions to specific problems.

BASIC RESEARCH


Basic research is conducted to expand knowledge and

understanding by either developing or testing theory. Its

focus is knowledge for knowledge's sake. It is typically

what we think of when we think of scientific research.

Basic research is used to explore the fundamental bases

of behavior, without regard to how those bases are

manifested in the real world. Basic research aims to

explain, predict, and describe fundamental bases of

behavior.

It exemplifies by the experiment paradigm explores

theoretical relationships with little regard for the practical

implications of the research findings. Given this focus,

basic scientific research is conducted in the laboratory

where minimum attention is paid to generalizing results

to real life settings.

Basic research is generally not related to a specific

problem and its findings cannot be immediately applied.

Pure research, basic research, or fundamental

research is research carried out to increase

understanding of fundamental principles. It is not intended to yield immediate practical benefits; pure

research can be thought of as arising out of curiosity.

The research which is done for knowledge enhancement, the research which does not have immediate

commercial potential. The research which is done for human welfare, animal welfare and plant

kingdom welfare. Basic research lay down the foundation for the applied research.

APPLIED RESEARCH

Applied research is a form of systematic inquiry involving the practical application of science. It

accesses and uses some part of the research communities' (the academia's) accumulated theories,

knowledge, methods, and techniques, for a specific, often state-, business-, or client-driven purpose.

Applied research is compared to pure research (basic research) in discussion about research ideals,

methodologies, programs, and projects.

Applied research deals with solving practical problems and generally

employs empirical methodologies.

Applied research directly addresses the problem at hand. Applied research is launched by the firm,

agency, or individual facing a specific problem.

The primary purpose for applied research (as opposed to basic research) is discovering, interpreting,

and the development of methods and systems for the advancement of human knowledge on a wide

variety of scientific matters of our world and the universe.

Applied research is designed to solve practical problem of the modern world, rather than to acquire

knowledge for knowledges sake. The goal of applied research is to improve the human condition. It

focus on analysis and solving social and real life problems. This research is generally conducted on

large scale basis, it is expensive. As such, it often conducted with the support of some financing

agency like government , public corporation , world bank, UNICEF, UGC,Etc,.

Applied research is research conducted to further the development of effective policies and programs.

It collects and analyzes empirical data to provide knowledge that can be used to develop new policies

and programs or evaluate existing ones.


It is concerned with the practical and theoretical sides of communicative life. It explores theoretical

relationship of the purpose of understanding and solving problems related to everyday communicative

actions and interactions. Survey research including political poles and analysis of peoples media preferences often has an applied orientation. Public speaking studies that generate prescriptive rules of

effective speech may be applies as well. Because of its pragmatic posture, applies research is usually

taken place in field settings.

Types of applied research Needs assessment.

Program evaluation and outcome assessment.

Client, patient, employee, and product satisfaction research.

Cost-benefit analysis.

Social impact assessment.

Action research.

Operations research and organizational analysis.

Market research and utilization studies.

Public opinion and political polling.

Quality assurance research.

6.3 HISTORICAL RESEARCH DEFINITION Historical research is the process of systematically examining past events to give an account of what

has happened in the past.

It is a flowing, dynamic account of past events which involves an interpretation of the these events in

an attempt to recapture the nuances, personalities, and ideas that influenced these events. It is not a

mere accumulation of facts and dates or even a description of past events.

Historical research describes past events, problems, issues and facts. Data are gathered from written

or oral descriptions of past events, artifacts, etc. It is different from a report in that it involves

interpretation of events and its influence on the present.

Historical research has been defined as the systematic and objective location, evaluation and synthesis

of evidence in order to establish facts and draw conclusions about past events (Borg (1963).

The values of historical research have been categorized by Hill and Kerber as follows:

it enables solutions to contemporary problems to be sought in the past; it throws light on present and future trends; it stresses the relative importance and the effects of the various interactions that are to be found

within all cultures;

it allows for the revaluation of data in relation to selected hypotheses, theories and generalizations that are presently held about the past.

Examples of Historical Research

A study of the factors leading to the historical development and growth of cooperative learning

A study of the effects of the historical decisions of the United States Supreme Court on American

prisons

A study of the evolution of print journalism in the United States through a study of collections of

newspapers

A study of the historical trends in public laws by looking recorded at a local courthouse


Ethnographic research develops in-depth analytical descriptions of current systems, processes.

OBJECTIVES OF HISTORICAL RESEARCH One of the goals of historical research is to communicate an understanding of past events.

Historical research is conducted to

Uncover the unknown,

Answer questions,

Identify the relationship that the past has to the present,

Record and evaluate accomplishments of individuals, agencies, or institutions,

Aid in understan

Documents

Website Sources for research Data