Business Research Methods Notes

BUSINESS RESEARCH METHODS UNIT I

Research means a search for knowledge. It refers to a scientific and systematic search for pertinent information on a specific topic. The term research refers to the systematic method consisting of enunciating the problem, formulating a hypothesis, collection the facts or data, analyzing the facts and reaching certain conclusions. Research is thus an original contribution to the existing stock of knowledge making for its advancement.

OBJECTIVES

1. To explore a phenomenon or to achieve new insights into it.

2. To discover the characteristic of a particular individual, situation or a group. 3. To examine the frequency with which something occurs or with which it is

associated with something else.

4. To test a hypothesis of a casual relationship between variables.

RESEARCH TYPES Basic Vs Applied:

Basic means the investigation of problems to further and develop existing knowledge. It is mainly concerned with generalization and formulation of theories. Gathering knowledge for knowledge’s sake is termed basic research. E.g. Physics, astronomy. Similarly, studying the behavior of individual to make some generalization about their social learning, memory pattern, and intelligence level are also examples of fundamental research.

1. Descriptive Vs analytical Research:

Descriptive research describes the present state of affairs as it exists without having any control over variables. The researcher can only report what has happened or what is happening. In analytical research on the other hand the researcher has to use fact or information already available and analyze these to make a critical evaluation of the material.

Quantitative research is based on the measurement of quantity or amount. It is applicable to phenomenon that can be expressed in terms of quantity. Qualitative research is concerned with qualitative phenomenon. Qualitative research is especially important in the behavioural sciences where the aim is to discover the underlying motives, interest, personality and attitudes of human beings.

3. Conceptual Vs empirical Research

Conceptual research is related to some abstract ideas or theory. Philosophers and thinkers generally use it to develop new concepts or to interpret existing ones. Empirical research is data based coming up with conclusions that are capable of being verified, by observation or by experiment. Empirical research is appropriate when proof that certain variables affect other variables in some way is sought. It is considered that evidence gathered through experiments or empirical studies provides the most powerful support for a given hypothesis

4. Laboratory research:

The emphasis in laboratory research is on controlling certain variables in such as to observe the relationship between two or three other variables.

5. Clinical or diagnostic Research;

This type of research follows case study methods or in-depth approaches to reach the basic causal relationship. This research takes only a few samples and studies the phenomenon in depth and observes the effects.

6. Exploratory research :

The objective of exploratory research is the development of hypothesis rather than their testing. The major emphasis is on the discovery of ideas and insights. It is more flexible and highly informal.

7. Historical research :

This type of research utilizes historical sources like documents, literature, leaflets etc

8. Panel Research

Panel methods are broader than descriptive than descriptive research. These methods are normally used in sales forecasting by measuring consumer preferences for various products measuring audience size and character for media

programmes, testing new products and product concepts and testing any variable in a firm’s marketing mix. Generally the survey is valid for one time period, which is known as study period and they do not reflect changes occurring over time.

9. Experimental Research:

A process where events occur in a setting at the discretion of the experimenter and control are used to identify the sources of variation in subject’s response. The investigator or experimenter systematically manipulates some factor to elicit a response from the subjects. Experimentation is considered to be process of manipulating one variable constant in order to establish a casual relationship.

RESEARCH PROCESS

Define research Problem Review of Literature Developing Hypothesis Research Design Sample Design Report Preparation Data Collection Interpretation Hypothesis Testing Analysis of Data

1. Defining the research problem:

Defining the basic problem, constitute the first step in a scientific enquiry. While formulating the research problem there are two main issues.

1. Review Of Literature

It is a stage in which the researcher makes himself familiar with all the previous studies and their findings relevant to his field of work. He learns the methodology and approach developed by these past studies. He evaluates the conclusion of the previous studies in the light of the data he has collected. He questions these conclusions and tries to develop the alternative, possible better conclusions.

2. Developing the hypothesis:

Hypothesis is a statement developed on the basis of suspected or anticipated relationship among various factors studied. Normally at the beginning of the research, the scholar would formulate a working hypothesis. It enables him to avoid collecting irrelevant data and facts. It helps him in focusing his attention on a particular aspect thereby eliminating wastage of time and resources.

3. Research Design

Research design is a description of conceptual structure within which the research will be conducted. Here the researcher indicates the method of data collection the skills at the command of the researcher, the execution plan collection of data, the time and other resources available the financial implication etc,

4. Sample Design

The researcher has to make a careful selection of a few elements from the population and then study them intensely and reach conclusion, which can be safely applied to the population. The selection of sample is a very important task. The researcher should determine the size of sample, the method of sampling, the test of sample etc.

5. Collecting Data

The researcher at this stage should clearly spell out the sources of data for his work. He could use both primary as well as secondary data. While the former refers to the data collected for the first time by the researcher himself from the informants or the sample respondents specifically for his work. The latter means the data already, published or unpublished & available for use. The quality of data collected will ultimately decide the findings of the research work and so the researcher should arrange for surprise checks and controls over the collection of field data.

6. Analysis Of data:

Once the data are collected they should be classified and tabulated. Then the analysis of the data should be undertaken. At this stage, the researcher should select the tools of analysis, which are consistent with the objectives of the study. The tendency to carry out irrelevant analysis should be avoided. He should be strong in reasoning, drawing inferences and reaching conclusions.

7. Testing Hypothesis:

After analyzing the data as stated above the researcher is in a position to test the hypothesis, if any he had formulated earlier. Statistician has developed various tests such as chisquare test, t-test, F- test for the purpose. The hypothesis may be tested through the use of one or more of such tests, depending upon the nature and object of research inquiry. The test result may result in either accepting the hypothesis to start with generalization established on the basis of data may be stated as hypothesis to be tested by subsequent researches in time to come.

8. Generalization & interpretation:

If a hypothesis is tested and upheld several times it may be possible for the researcher to arrive at generalization, The real value of the researcher lies in its ability to arrive at certain generalizations. If the researcher had no hypothesis to start with he might seek to explain his findings on the basis of some theory. it is called as interpretation. The process of interpretation may quite often trigger off new questions that in turn may lead to further researchers.

9. Report Preparation:

Finally the researcher has to prepare the report of what has been done by him. Writing of report must be done with great care. The report should clearly indicate the justification of the study, period of study, sample size, sources of data, tools of analysis, bibliography, review of past studies etc. It should also have a separate chapter on results and discussions where the researcher would report all his findings and give his interpretations. Care should be taken to incorporate relevant tables, diagrammed etc at the appropriate places.

CRITERIA OF GOOD RESEARCH:

1. The purpose of the research should be clearly defined and common concepts be used.

2. The research procedure used should be described in sufficient detail to permit another researcher to repeat the research for further advancement, keeping the continuity of what has already been attained.

3. The procedural design of the research should be carefully planned to yield results that are as objective as possible.

4. The researcher should report with complete frankness, flaws in procedural design and estimate their effects upon the findings.

5. The analysis of data should be sufficiently adequate to reveal its significance and the methods of analysis used should be appropriate.

6. Conclusion should be confined to those justified by the data of the research and limited to those for which the data provide an adequate basis.

7. Greater confidence in research is warranted if the researcher is experienced has a good reputation in research and is a person of integrity.

QUALITIES OF GOOD RESEARCHER: Good research is systematic:

It means that research is structured with specified steps to be taken in a specified sequence in accordance with the well-defined set of rules. Systematic

characteristics of the research do not rule out creative thinking but it certainly does reject the use of guessing and intuition in arriving at conclusions.

1. Good research is logical:

This implies that research is guide by the rules of logical reasoning and the logical process of induction and deduction are of great value in carrying out research.

2. Good Research is empirical:

It implies that research is related basically to one or more aspects of a real situation and deals with concrete data that provides a basis for external validity to research results.

3. Good Research is Replicable:

This allows research to be verified by replicating the study and thereby building a sound basis for decisions.

PROBLEMS ENCOUNTERED BY RESEARCHER IN INDIA:  The lack of a scientific training in the methodology of research

 Insufficient interaction between the university research departments on the side and business establishments, governments department, and research institution on the other side.

 The business unit do not have confidence that the information supplied by them to researchers will be misused and so such they are often reluctant in supplying the needed information to researchers.

 Research studies overlapping one another are undertaken quite often for want of adequate information.

 There does not exist a code of conduct for researcher  The difficult of adequate and timely secretarial assistance.

 Library management and functioning is not satisfactory at many place.

 There is also the problem that many of our libraries are not able to get copies of old and new Acts/ rules, reports and other government publications in time.

 There is also the difficulty of timely availability of published data.  There may at times take place the problem of conceptualization.

HYPOTHESIS

• It is a tentative generalization, the validity of which remains to be tested. At the elementary level it may be mere hunch, guess, and imaginative data, which becomes the basis for action or investigation. – Lundberg

• Hypothesis is a proposition, which can be put to test to determine validity. – Goode & Hatt.

• A tentative solution posed on a cursory observation of known and available data and adopted provisionally to explain certain events and to guide in the investigation of others. It is in fact, a possible solution to a problem.

CHARACTERISTIC OF HYPOTHESIS

• Clarity:

The hypothesis must be conceptually clear. When the researcher attempts to establish relationship among various facts and translates these relationships into concepts he succeeds in formulating the hypothesis. Hence when a hypothesis is conceptually clear it provides a clear direction to the researcher.

• Scope For Verification:

Hypothesis should be amenable for verification and empirical analysis. Though hypothesis can be verified in terms of moral judgments yet such verifications process will be questionable.

• Specific:

The hypothesis should be very specific and not a general statement. It should not be ambiguous and it should be clearly stated. It is wiser to construct a hypothesis in simple language than resorting to flowery and confusing terminology.

It should be testable with the available technique of analysis. Even while formulating a researcher should ascertain the relevant techniques with which it could be tested.

• Linked To Theory

Hypothesis should facilitate establishing relationship with a body of theory. Therefore when the hypothesis is formulated the researcher should conform whether it is related to any existing theory or not.

• Consistent

It should be consistent with a most known facts ie it must be consistent with a substantial body of established facts. It should be one which judges accept as being the most likely.

TYPES OF HYPOTHESIS:

• Crude Hypothesis:

A crude hypothesis is formed to initiate the process of research. When the researcher is commencing his research work he needs some guidelines or focus. For this purpose he might develop a hypothesis based on the available evidence or data.

• Refined hypothesis:

Hypothesis that state the existence of empirical uniformities, hypothesis that are concerned with complex ideal types and hypothesis that are concerned with complex ideal types and hypothesis that are concerned with the relation of analytical variables.

• Working hypothesis

It is formed in the process of verifying the relationship among various variables included in research. It provides useful guideline to the researcher in determining the nature of data to be collected, volume of data required, the sample technique to be used analytical tools to be selected etc.

• Statistical hypothesis

Statistical hypothesis are those, which are formulated based on the sample data or facts. They serve the usual purpose of testing any expected relationship among variables.

Once these hypotheses are tested or verified the conclusion about the population is drawn.

• Null hypothesis

It is formulated only to test whether there is any relationship between variables related to the problem being studied. Usually the null hypothesis is formed as a negative statement.

• Alternative hypothesis

It is a statement, which is accepted after the null hypothesis is rejected based on the test results.

PROCEDURE FOR HYPOTHESIS TESTING:

It refers to all those steps that we undertake for making a choice between the two actions ie. Rejection and acceptance of a null hypothesis. The various steps involved in hypothesis testing are stated below;

1. Making a formal statement :

The step consists in making a formal statement of the null hypothesis and also of the alternative hypothesis.

2. Selecting a significance level :

The hypothesis is tested on a pre- determined level of significance and as such the same should be specified. Generally 5% or 1% is adopted for the purpose. The factors that affect the level of significance are; a) the magnitude of the difference between sample means. b) Whether the hypothesis is directional or non directional. c) The variability of measurements within samples d) whether the hypothesis is directional or non directional.

3. Deciding the distribution to use:

After deciding the level of significance the next step in hypothesis testing is to determine the appropriate sampling distribution. The choice generally remains between normal distribution and the t-distribution.

The next step is to select a random sample and compute an appropriate value from the sample data concerning the test statistic utilizing the relevant distribution.

5. Calculation of the probability:

Then calculate the probability that the sample result would diverge as widely as it has from expectations, if the null hypothesis were in fact true.

6. Comparing the probability:

In this step compare the probability thus calculated with the specified value for ∝ the significance level. If the calculated probability is equal to or smaller than the

∝ value in case of one tailed test , then reject the null hypothesis but if the calculated probability is greater then accept the null hypothesis.

SOURCES OF HYPOTHESIS

• Theory: This is one of the main sources. It gives direction to research by stating what is known. Logical deduction from theory leads to new hypothesis.

Eg . the rate of return on capital employed is an index of business success.

• Observation: Hypothesis can be derived from observation . from observing price behavior in a market a hypothesis can be formulated on the relationship between price & demand for an article.

• Analogies: Julian Huxley pointed out that casual observation in nature or in the framework of another science may be fertile source of hypothesis. The hypothesis that similar human types or activities may be found in similar geophysical regions came from studying plant ecology.

• Intuition & personal experience: Personal life and experience of persons determine their perception. These may in turn direct a person to certain hypothesis more quickly. Eg Newton & falling of apple.

• Findings Of studies: Hypothesis may be developed from the findings of other studies in order to replicate and test.

• State Of Knowledge: An important source of hypothesis is the state of knowledge in any particular science. Where formal theories exist , hypothesis can be deduced from them. If the hypothesis were rejected theories would be modified. Where formal theories are scarce, hypothesis are generated from conceptual frameworks.

• Culture: another source of hypothesis is the culture in which the researcher has been nurtured. In India in socio – economic and leadership studies, hypothesis based on caste- ridden, hierarchical and segmental and the Indian economic system riddled with inequalities and privileges.

• Continuity Of research: The continuity of research in a field itself constitute an important source of hypothesis leads to the formulation of new ones capable of explaining dependent variables in a subsequent researchers on the same subject.

CHARACTERISTIC OF A GOOD HYPOTHESIS:

• Conceptual Clarity: It should be conceptually clear. It should consist of clearly defined and understandable concepts. Clarity is obtained by defining operationally the concepts in the hypothesis.

• Specificity: A hypothesis should be specific and explain the expected relations between variables and the conditions under which these relations will hold.

• Testability: A hypothesis should be testable and should not be a moral judgement. It should be possible to collect empirical evidence to test the hypothesis. Eg Bad partners produce bad children.

• Availability Of technique: Hypothesis should be related to available techniques. Otherwise they will not be researchable. Therefore the research must make sure that methods for testing his proposed hypothesis are available.

• Theoretical relevance: It should be related to a body of theory. A science can be cumulative only building on an existing body by building on an existing body of facts and theory. When research is systematically based upon a body of existing theory, a genuine contribution to knowledge is more likely to result. Therefore a hypothesis should posses theoretical relevance.

• Consistency: Hypothesis should be logically consistent. Two or more propositions logically derived from the same theory must not be mutually contradictory.

• Objectivity: Scientific hypothesis should be free from value judgements. However as social phenomenon are affected by the milieu in which they take place, the researcher must be aware of his values and state them explicitly.

• Simplicity: A hypothesis should be a simple one requiring fewer conditions or assumptions. It demands insight. The more the insight the researcher has into a problem; the simple will be his hypothesis about it.

RULES IN HYPOTHESIS DEVELOPMENT:

1. Search for variable measurements with the most quantitative characteristic.

2. Make the variable like properties explicit by stating all of the variable’s mutually exclusive and totally inclusive categories by degree.

3. Describe the means used to sort observation into your variable categories insufficient detail so that methods may be evaluated and replicated by others .

4. Always consider alternative operations that might be more appropriate for a given variable.

5. Analyze variable through their relationship.

6. Link two or more formal propositions through a shared independent or dependent variable where possible.

RESEARCH DESIGN

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. In fact the research design is the conceptual structure within which research is conducted. it constitutes the blueprint for the collection measurement and analysis of data. In keeping the above stated design decisions one may split the overall research design into the following parts;

1. The sampling design: Which deals with the method of selecting items to be observed for the given study.

2. The above observational design: which relates to the conditions under which the observation is to be made?

3. The statistical Design: which concerns with the question of how many items are to be observed and how the information and data gathered are to be analysed.

4. The operational design : which deals with the techniques by which the procedures specified in the sampling , statistical and observational design can be carried out.

FEATURES OF THE RESEARCH DESIGN:

1. It is a plan that specifies the source and types of information relevant to the research problem.

2. It is an outline that specifies the objectives of the study and the hypothesis Relevant to the research questions.

1) It is a blueprint specifying his methods to be adopted for gathering and analyzing data.

3. It is a scheme defining the domain of generalisability.

IMPORTANT ELEMENTS OF A RESEARCH PLAN:

After making decisions on the above questions a formal research plan incorporating is drafted. The format may vary depending on the purpose for which the study is undertaken.

Introduction: The introduction of a research plan or proposal should place the research problem in its historical perspective. It must state the need for studying it. and the research’s precise interest in studying the problem.

Statement Of the problem: The research problem should be defined pointing out its core nature and its importance. The issue relating to the problem may also be stated. This statement gives direction to the research process.

Review Of previous studies: There may be previous studies on the selected theme. A review of available literature will bring out information on them. The primary aspects of those studies may be briefly described and the gaps pointed out.

Scope of the study: A complete study of any problem is well high non- manageable, since it would entail an overwhelming mountain of data. Therefore the scope and dimension of the study should be delimited with reference to the topical scope- breath and depth, geographical area to be covered , reference period , the type of institution Objective Of the study: The specific objectives of the study should be stated clearly. These refer to the questions to which the researcher proposes to seek answers through the study.

Conceptual model: This section is the heart of the research plan. This is where the researcher formulates and develops the structure of relationship among the variables he is investigating.

Hypothesis: These are logically deduced from the theoretical framework above. They refer to the anticipated outcome or possible answers to the research questions. they should be conceptually clear , specific and simple.

Operational definition OF concepts: The major concepts used in the title of the study , its objectives , the investigative questions and the hypothesis should be identified. Each of them should be defined in operational terms pertinent to the measurement criteria or operations.

The significance of the study: It is important to point out the relevance and significance of the investigation. A careful statement of the value of the study and the possible applications of its findings helps to justify its importance and social relevance.

Geographical area to be covered: The territorial area to be covered by the study should be decided and specified in the plan. The area to be chosen depends on the purpose of the study and time and other resources.

Reference Period: This depends on the nature of the study and availability of data. The period should be longer- say five or 10 years – if the study aims to make a trend analysis of an activity like production or sale or profitability.

Methodology: In this section the overall topology of the design – experimental, descriptive, survey, case study or historical study – is specified. Further the method or methods to be adopted for the collection of data- observation, interviewing or mailing – are specified.

Sampling Plan: If the study requires collecting primary data from the field the universe must be deliberated, and the methods of sampling to be used for drawing the sample from the universe and the sample size must be stated.

Tools for gathering data; In this section the tools to be used for gathering data- interview schedule /guide , questionnaire or check list etc. are listed and each of them described. the tools chosen should be appropriate to the methods to be adopted for gathering data.

Plan of Analysis: The statistical techniques proposed for data collection and analysis should be explained clearly with its suitability in the research.

Chapter Scheme: The chapter scheme of the report to be prepared for communicating the findings of the study to the academic community and users should be outlined and the purpose of each chapter stated.

Time budget: The time period required for each stage of work and the total time duration of the study are specified.

Financial Budget:

The should include an estimate of the expected costs of the project under major categories like salary, printing and stationary , postages , travel expenses , computation , secretarial & typing.

SIGNIFICANCE OF RESEARCH DESIGN:

 It may lead to more accurate results or help to reduce inaccuracy.  It may lead to optimum efficiency and reliability.

 It may minimize the wastage of time and beating about the bush.

 It may minimize the uncertainty, confusing and practical hazards associated with research problem.

 It may be helpful for the collection of research material and testing of hypothesis.  A research design is a guidepost for research direction.

TYPES OF RESEARCH DESIGN:  Exploratory Studies:

The major purpose of exploratory studies are: the identification of problems , the more precise formulation of problems and the formulation of new alternative courses of action. The design of exploratory studies is characteristics by great flexibility and ad-hoc versatility. By definition the researcher is involved in investigating an area or subject about which he or she is not sufficiently knowledgeable to have formulated detailed research questions and /or to state hypothesis about it. In short the researcher seeks to gain familiarity and /or achieve new insights into the problems situation. For a given problem the results of an exploratory study may indicate that further research can be reduced and /or certain aspects of the larger study can be eliminated. An exploratory study is conducted in the following situations;

 To design a problem for investigation & to formulate hypothesis  To determine the priorities for further research.

 To gather data about the practical problems of carrying out research on particular conjectural statements.

 To increase the analyst’s interest in the problems.  To explain basic concepts.

While applying this design three different methods are followed. Survey Of related Literature:

By studying intensively the past studies and contributions related to the field of study the research problem could be easily formulated.

Conducting Experience survey – This refers to undertaking collection of details and discussion with the experienced people in the chosen field of research. This would help the researcher to determine the extent to which he is original and can avoid duplication. Analysis Of insight –stimulating examples is yet another method in which depending upon the study on hand. In this method the experience of people would be used as a guide to develop of formulates a hypothesis.

Descriptive Studies:

Descriptive research design is concerned with the research studies with a focus on the portrayal of the characteristics of a group or individual or a situation. The main objective of such studies is to acquire knowledge. For example to identify the use of a product to various groups a research study may be undertaken to question whether the use varies with income, age, sex, or any other characteristics of population. Similarly such studies are used to examine the characteristics of the corporate sector or consumer behavior etc.

Descriptive research is a marked by the prior formulation of specific research question. The investigator already knows a substantial amount about the research problem, perhaps as a result of an exploratory study before the project is initiated. Thus the investigator should be able to define clearly what it is that he or she wants to measure and to set up appropriate and specific means for measuring it.

A researcher does a descriptive study in the following situations;

 During the analysis of characteristics of certain groups , e.g users of a product of different ages ,sexes ,education etc.

 To identify the proportion of people in a specified population who behave in a certain way e.g shoppers who buy from a particular shop.

 To forecast future trends e.g sales of a company‘s product in each of the next five years.

 To study whether certain variables are associated e.g income & use of a product. Casual Relationship/ experimental research Design:

This research studies are mainly focused on focused on finding out the cause & effect relationship of the phenomenon under study. Actually when observation is arranged and controlled, it becomes experimental research. An experiment is a test or trail or an act or operation for the purpose of discovering something unknown or of testing a principle , supposition etc. It is a unconfused fashion. There are different types of experiments such as methodology, pilot study, heuristic, fact finding, boundary, simulation, theoretical , illustrative etc.

FACTORS AFFECTING RESEARCH DESIGN:

• Non – Availability Of sufficient data: This is one of the basic factors affecting research design. A design developed at one stage may undergo change in the process of research as data may not be available. Then the design would be suitably method. To overcome this usually researcher conduct a pilot study to ascertain whether the required data would be available or not.

• Availability Of time: In the research process various stages are time consuming. For example problem identification data collection, analysis and interpretation etc. require a lot of time. The research design would be depending upon the availability of sufficient time to carry out all these process rigorously.

• Availability Of resources: Certainly the availability of human and financial resources will influences research design. A study which requires highly specialized skill or experience, identifying such personalities would itself consume a lot of time. Similarly the level of accuracy aimed at would also call for liberal funding of the research process. Therefore researches with ambitious objectives are usually undertaken only by organizations or with sponsors or by government, considering the volume of funds required.

• Ability Of researcher: Not every researcher is gifted with all the qualities required for conducting good research. A study which is highly analytical would call for knowledge about the analytical tools and the interpretation ability. Similarly an experimental research would require a special temperament. Hence

depending upon the potential and ability of the researcher the research design would be prepared.

UNIT – II EXPERIMENTAL RESEARCH DESIGN

Experiment is a study in which the investigator manipulates or varies one or more variables and measures other variables. In other words It is a process of manipulating one variable in a controlled environment while holding all other variables constant in order to establish a casual relationship.

All experiment involves three basic components:

1. Variable manipulated in a experiment are referred to as the independent variable or test units.

2. The actual alteration is called the treatment.

3. The actual variable chosen to measure the subject response are known as dependent variables.

The result of the treatment is measured on dependent variable and these results of the treatment are given a variety of names i.e, outcome, observation change, effect etc.

Advantage:

1. The researcher can manipulates the independent variable

2. Control group serves as a comparison to assess the existence and potency of the manipulation.

3. The contamination from extraneous variable can be controlled more effectively. 4. The convenience and cost of experimentation are superior to other methods. 5. The experimenter can assemble combination of variables for testing .

6. Repeating an experiment with different subject group and condition is possible. 7. Researcher can use naturally occurring events.

Disadvantages:

2. Generalisation from non-probability samples can poses problems. 3. The experimentation can outrun the budget.

4. It is mostly effectively targeted at present or immediate future problems. 5. It is concerned with the study of people.

6. There is limits to the types of manipulation and control that are ethical.

CONDUCTING AN EXPERIMENT: 1. Select relevant Variable

In this step researcher will a) Select variable that are the best operational concepts. b) Determine how many variables to test c) Select or design appropriate measures for them.

2. Specify the level of the treatment:

The treatment levels of the independent variables are the distinctions the researcher makes between different aspects of the treatment condition.

1. Control the experimental Environment

At this research concerned with environment control, holding constant the physical environment of the experiment. The introduction of the experiment to the subjects and the instruction would likely be videotaped for consistency. The arrangement of the room, the time of administration the experimenter’s contract with the subjects and so forth must all be consistent across each administration of the experiment.

4. Choose the experimental design:

The experimental design are unique to the experimental. They serve as positional and statistical plans to designate relationships between experimental treatment and the experimenter’s observations or measurement points in the temporal scheme of the study. The design strengthen the generalizability of results beyond the experimental setting

4. Select and assign the subjects:

The subject selected for the experiment should be representative of the population to which the researcher wishes to generalize. The researcher first prepares a sampling frame and then assigns the subject for the experiment to

groups using a randomization technique. If randomization is used those assigned to the experimental group are likely to be similar to those assigned to the control group. Random assignment to the group is required to make the group as comparable as possible with respect to the dependent variable.

5. Pilot test –revise and test:

Pilot testing is intended to reveal errors in the design and improper control of extraneous or environmental conditions. Pretesting the instrument permits the researcher to revise scripts ,look for control problems with laboratory conditions and scan the environmental for factor that might confound the results.

6. Analyse the data:

If adequate planning and pretesting have occurred the experimental data will take an order and structure uncommon to surveys and unstructured observational studies. Researcher has several measurement and instrument options with experiment. Among them are

1) Observational technique and coding schemes 2) Paper and pencil tests

3) Self report instrument with open or dosed questions 4) Scaling technique

5) Physiological measure

VALIDITY IN EXPERIMENTATION:

Validity refers to the extent to which the conclusions drawn from the are true experiment

I - Internal validity:

Refers to the extend to which the research design accurately identifies casual relationship.

a) History

When extraneous factors that enter the experiment process between the first and later manipulation affect measure of the dependent variable.

b) Maturation :

Changes in the dependent variable based on the natural function of time and not attributed to any specific event.

c) Testing

When learned understanding gained from the first treatment and measure of the dependent variable distort future treatment and measurement activities.

d) Instrumentation :

Contamination from changes in measurement processes observation technique and measuring instruments

e) Selection Bias:

Contamination created by inappropriate selection or assignment process of test subject to experimental treatment groups

f) Statistical Regression:

Contamination created when experiment group are selected on the basis of their extreme response or scores.

g) Mortality :

Contamination due to changing the composition of the test subjects in the experiment.

h) Ambiguity :

Contamination from unclear determination of cause effect relationship

II - External Validity:

Refer to the extent to which a casual relationship found in a study can be expected to be true for the entire target population.

a) Treatment Vs Treatment

When test subject in different treatment groups are exposed to different amount of manipulations.

b) Treatment Vs Testing

When the premeasurement process sensitizes test subject to respond in an abnormal manner to treatment manipulation.

Generalising the results to other categories of people beyond those used in the experiment

d) Treatment Vs Setting

Generalising the results to other environment beyond the one used in the experiment. e) Treatment Vs History

Using the existing functional relationship to predict future phenomenon outcomes.

III - Construct Validity

Refers to the extent to which the variables under investigation are completely and accurately identified prior to hypothesizing any functional relationships.

a) Inadequate pre-operationalization of variable

Contamination due to inadequate understanding of the complete make-up of the independent and dependent variable included in the experimental design.

b) Mano operation bias

Contamination created by using only one method to measure the outcome of the dependent variable.

c) Mano-method bias

Contamination due to assessing multi-attribute treatment manipulation using single item measuring instrument.

d) Hypothesis –guessing

Contamination by test subject believing they know the desired functional relationship relationship prior to the manipulation treatment.

e) Evaluation Apprehension:

Contamination caused by test subjects being fearful that their actions or response will become known to others.

f) Demand Characteristic:

Contamination created by test subjects trying behind the experiment thus abnormal socially acceptable responses or behaviour.

Contamination due to test subject discussing the treatment and measurement activities with individual yet to receive the treatment.

IMPROVING THE VALIDITY OF EXPERIMENT DESIGN: a) Inclusion of control group

When designing an experiment the researcher must determine who will be assigned to the group that will be exposed to the manipulation and who will be assigned to the control that does not receive the manipulation. Control group represent the greatest strength of the experiment and the best way to ensure internal validity.

b) Time order of the manipulation exposure:

The researcher also must determine which variables, independent or dependent will occur first. This can be accomplished by using pre-experimental measure of the variables prior to manipulation or by establishing experimental treatment and control group that do not differ in terms of influencing the dependent variable before the manipulation takes place.

c) Exclusion of Non similar test subject

To increase internal validity the researcher can select only those test subject who have similar and controllable characteristics.

d) Matching extraneous variable

Through the process of matching, the researcher measure certain extraneous variable on a individual by individual basis Those who respond similarly to the variables are then allocated to the experimental and control groups. Again this process can control for both selection and statistical regression threats and enhances internal validity.

e) Randomisation Of Test subjects to treatment groups

Randomization of the assignment of test subjects to the experimental and control groups can help make the groups equivalent . To enhance external validity the researcher should also randomly select setting and times for the experiment based on the population or event under investigation.

PRINCIPLES OF EXPERIMENTAL DESIGN a) Principle of Replication :

According to this principle the experiment should be repeated more than once. So each treatment is applied in many experimental units instead of one. By this statistical accuracy of the experiment can be increased. This aims for increase in accuracy with which effects and interactions can be estimated.

b) Principle of Randomisation

It provides protection, against the effect of extraneous factors in experiment. This principle indicates that we should design or plan the experiment in such a way that the variations caused by extraneous factors can all be combined under the general heading of chance.

c) Principal Of local control

Under this method we first divide the whole unit into several homogenous parts , known as blocks and then each such block is divided into parts equal to the number of treatment. Then the treatment are randomly assigned to these parts of the block.

TYPES OF EXPERIMENTAL DESIGN I - Informal experimental design

1) Before and after without control design

In this design a single test group or area is selected and the dependent variable is measured before the introduction of the treatment. The treatment is then introduced and the dependent variable is measured again after the treatment has been introduced.

Training Effect = Y- X

2) After – Only with control design

In this design two group or areas are selected and the treatment is introduced into the test area only. The dependent variable is then measured in both the areas at the same time. Treatment impact is assessed by subtracting the value of the dependent

Experimental

Group Level of [X] _Performance

Training

variable is then measured in both the areas at the same time. Treatment impact is assessed by subtracting the value in the test area.

Training Effect = Y- Z

3) Before and After with control design

In this design two areas are selected and the dependent variable is measured in both the areas for an identical time period before the treatment. The treatment is then introduced into the test area only, and the dependent variable is measured in both for an identical time period after the introduction of the treatment. The treatment effect is determined by subtracting the change in the dependent variable in the control area from the change in the dependent variable in the test area.

Time Period – I Time Period - II

Training Effect [Y-X] – [Z-A]

II Formal Experimental Design 4) Completely Randomized design

Experimental

Group Training

Introduced

Level of performance after training [Y]

Experimental

Group No Training

Level of performance after training [Z]

Experimental

Group Performance Level of [X]

Training

Introduced Level of Performance [Y]

Control Group Level of Performance [A] No Training Level of Performance [Z]

In this design the subjects are randomly assigned to experimental treatments. It involues two basic principle , ie principle of replication and principle of randomization of experimental designs.

a) Two group simple randomization design

In this design all the population is defined and then from population a sample is selected randomly. Then the samples are randomly assigned to the experimental and control groups. The two groups ie experimental & control , of such a design are given different treatments of the independent variable. This design is common in behavioural sciences.

It is simple & randomize the differences among the sample items. But this does not control extraneous variable.

a. Two Group Simple Randomized Design

b) Random replication design:

In previous design extraneous variable was not controlled. But in this method the effect of such variable are minimized by providing a number of repetitions for each treatment. Each repetition is technically called a replication. In this design sample is taken randomly from the population available to conduct experiments and randomly

Population Randomly Selected

Sample

Treatment [A]

assigned to four experimental & four control groups. Generally equal number of items are put in each group so that the size of the group is not likely to affect the results of the study. Due to repetitions the results are more reliable and population differences is also reduced as it is randomized. Group 1 E Group 2 E Group 3 E Group 4 E Group 5 C Group 6 C

Population

Sample

Population

Sample

Treatment A

Independent Variable (or) Casual Variable

Treatment

B

Group 7 C

Group 8 C

5) Randomized Block design

It is an improvement over the completely randomized design. In this local control can be applied along with other principles of experimental design. The subjects are divided groups known as blocks. , within each group the subjects are relatively homogeneous in respect to some selected variable. The number of subjects in a given block would be equal to the number of treatments and one subject in each block would be randomly assigned to each treatment. In general blocks are the level at which we hold the extraneous factor fixed. So that its contribution to the total variability of data can be measured. The main feature of the R.B. design is that in this each treatment appears the same number of times in each block.

Randomized Block Design:

Student Very Low I.Q A Very Low I.Q B Very Low I.Q C Very Low I.Q D Very Low I.Q E Form 1 Form 2 Form 3 Form 4 Form 5

6) Latin Squares design

It is used in agricultural research. For eg an experiment has to be made through which the effects of five different varieties of fertilizers on the yield of a certain crop say wheat is to be judged. In such case the varying fertility of the soil in different blocks in which the experiment has to be performed must be taken into consideration otherwise the

results obtained may not be very dependable because the output happens to be the effect not only of fertilizers, but it may also be the effect of fertility of soil , varying seeds. To overcome such difficulties the L.S design is used when there are two major extraneous factors such as the varying soil fertility & varying seeds.

The merit of this design is it enables differences in fertility gradients in the field to be eliminated in comparision to the effects of different varieties of fertilizers on the yield of the crop. But it has a limitation , that there is no interation between treatments and blocking factors and it requires rows & columns to be equal

I II III IV V X1 X2 X3 X4 X5 Fertility Level 7) Factorial Design

It is used in experiment where the effects of varying than one factor be determined.

a) Simple factorial Designs;

It is also termed as a two –factor factorial design. In this design the extraneous variable to be controlled by homogeneity is called the control variable and the independent variable, which is manipulated is called the experimental variable. Then there are two experimental variable and two levels of the control variable. Subjects are assigned at random to each treatment just like Random design. Means of different cells represent the mean scores for the dependent variable. The column means represent the effect for treatments without taking in account of control variable. The row means represent the effect for levels without regard to treatment. Thus we can study the main effect of

treatments as well as the main effect of levels. It is also possible to examine the interactions between treatment and levels, whether they are independent of each other nor they are not so.

Training Control Intelligence

Treatment A Treatment B Row Mean

Level I 155 23.3 19.4 Level II 35.8 30.2 33.0 Column Mean 256 26.7 Training Control Intelligence

Treatment A Treatment B Row Mean

Level I 10.4 20.6 15.5

Level II 30.6 40.4 35.5

Column Mean 20.5 80.5

b) Complex Factorial design: 40 B A 30 20 10 A B

Experiment with more than two factors at a time involve the use of complex factorial design. A design which considers three or more independent variables simultaneously is called a complex factorial design. When three factors with one experimental variable having two treatments and two control variable each one of which having two levels, the design used will be termed complex factorial design. In this method it is possible to determine the main effect for three variables ie one experimental and two control variables. The researcher can also determine the interactions between each possible pair of variables.

Experimental Variable Treatment A Treatment B C.V. 2 Level 1 C.V. 2 Level 2 C.V. 2 Level 1 C.V. 2 Level 2 Control Variable Level I Level II MEASUREMENT

Measurement can be defined as a standardized process of assigning numbers or other symbols to certain characteristics of the objects of interest, according to some pre- specified rules.

The definition implies that measurement is a three part process 1) Selecting observable events

2) Using numbers or symbols to represent aspects of the events. 3) Applying a mapping rule to connect the observation to the symbol. Data Type

Data classifications employ the real numbers system. The most accepted basis for scaling has three characteristics.

2) Differences between numbers are ordered. 3) Number series origin

Combination of these characteristics of order, distance and origin provide the following widely used classification of measurement scales.

1) Nominal Data

Nominal scale is simply a system of assigning number symbols to events in order to label them. It provides convenient ways of keeping track of people object and events. The counting of members in each group is the only possible arithmetic operation when a nominal scale is employed. Chi-square test is the most common test of statistical significance that can be utilized and for the measure of correlation , the contingency co-efficient can be worked out .

2) Ordinal Scale

It places events in order, but there is no attempt to make the intervals of the scale equal in terms of some rule. A rank order represents ordinal scales and are frequently used in research relating to qualitative phenomenon. It have no absolute values and the real differences between adjacent ranks may not be equal. All that can be said that one person is higher or lower on the scale than another but more precise comparisons cannot be made.

3) Internal Scale

It has the power of nominal and ordinal data plus one additional strength. It incorporates the concept of equality of interval. The intervals are adjusted in terms of some rule that has been established as a basis for making the units equal. Interval units are equal only in so far as one accepts the assumptions on which the rule is based .eg Centigrade and Fahrenheit temperature scales Mean, standard of deviation is appropriate measures. The generally used test for statistical significance are the “T” test “F” test & other parametric test are the statistical procedures of choice.

4) Ratio Scale

Ratio scale has an absolute or true zero of measurement. The term “absolute zero” is not as precise. We can conceive of an absolute zero length and also absolute zero of

time. It represents the actual amount of variables. Geometric & harmonic mean can be used as measures of central tendency & coefficient of variation may also be calculated.

CHARACTERISTICS OF SOUND MEASUREMENT 1) Validity

It is the extend to which difference found with a measuring tool reflect true differences among respondents being tested. The difficulty in meeting this test is that usually one does not know what the true difference

a) Content Validity

Degree to which extent content of the item adequately represents the universe of all relevant items under study.

b) Criterion Validity

Degree to which the predictor is adequate in capturing the relevant aspects of the criterion.

i) Concurrent Validity

Description of the present criterion data is available at same time as predictor Scores.

ii) Predictive Validity

Prediction of the future criterion is measured after the passage of time. c) Construct Validity

It tries to answer the question what accounts for the variance in the measure. Attempt to identify the underlying construct being measured and determine how well the test represents them.

2) Reliability

It is concerned with estimates of the degree to which a measurement is free of random or unstable error. A measure is reliable to the degree that it supplies consistent results. a) Stability

A measure is said to be stable if you can secure consistent results with repeated measurement of the same person with the same instrument.

Degree to which alternative forms of the same measure produce same or similar results.

c) Internal consistency:

Degree to which instrument items are homogenous and reflect the same underlying construct.

3)Practicality

It is concerned with how far it economical , convenience and interpretability a) Economy

There should be a trade off between ideal research project and the budget. b) Convenience test

Degree to which the measuring instrument is easy to administer. c)Interpretability

Degree to which the person other researcher is able to interpret the results

SCALING

It is a procedure for the assignment of numbers to a property of objects in order in order to impart some of the characteristics of numbers to the properties in question. Scaling Techniques:

I - Rating scale:

It involves qualitative description of a limited number of aspects of a thing or of traits of a person. Here we judge an object in absolute terms against some specified criteria There is no rules with points of scales, in practice 3 to 7 points scales are generally used.

There are various types of rating scale; a) Simple category scale :

It has two responses eg YES, NO. This scale is particularly useful for demographic question or where dichotomous response is adequate.

b) Multiple Choice – Single

When there are multiple options for the respondent and only one answer is sought this scale is preferred.

c) Multiple Choice – Multiple response scale

It allows the respondent to select one or more alternatives from multiple choices. e) Likert Scale –

It is a mostly used summated rating scale. It consists of statements that express either a favorable or unfavorable attitude toward the object of interest. The respondent is asked to agree or disagree with each statement. Each response is given a numerical score to reflect its degree of attitude favorableness and the scores may be totaled to measure the respondent’s attitude. This data provides interval data.

f) Semantic differential

It helps to measure the psychological attitude. It is used in marketing problems, political issues, and personalities. This method consist of bipolar rating scales, usually with seven points by which one or more respondents rate one or more concepts on each scale item. It produces interval data. The total set of response provides a comprehensive picture about the respondent rating and object which is measured.

g) Numerical Scale

It has equal intervals that separate their numeric scale points. The verbal statement serves as the labels for the extreme points. It is often five point scale. The scale provides absolute & relative measure of the subject.

h) Multiple rating scale:

It is similar to numerical scale, but differs in two ways 1) It accepts a circled response from the rater 2) The layout allows visualization of the results. The advantage is that a mental map of the respondent evaluation is evident to both the rater and the researcher. This scale produces interval data.

i) Fixed sum scale

In this scale two categories are presented that must sum to 100 upto 10 categories can be used. The advantage is its compatibility. It provides continuous data. The scale is used to record to attitudes, behaviour and behavioural intent.

It was created to enable researcher to discern fine differences. It uses pictures , icons or other visuals to communicate with the respondents.

Ranking Scales

In this the subject directly compares two or more objects and makes choices among them. The respondents were asked to select one as best or most preferred. a) Paired –comparison

In this respondent can express attitudes clearly by choosing between two objects. b) Forced Ranking Scale:

The list of objects are ranked relative to each other .This method is faster than paired comparisons and is usually easier and more motivating to the respondent. c) Comparative Scales

Another version of the preceding scale would label the categories “excellent”, ”very good”, “Good”, “fair” and “poor”. Thereby eliminating the implicit comparison. The problem with comparative scale is that the reference point is unclear and different reference points or standards.

SCALE CONSTRUCTION TECHNIQUES

In research while measuring attitudes of the people we generally follow the technique of preparing the opinonnaire (attitude scale) in such a way that the score of the individual responses assigns him a place on a scale. In this respondent express his opinion on various statements. While developing such statement the researcher must note the following points;

1) That the statement must elicit responses which are psychologically related to the attitude being measured.

2) That the statements need be such that they discriminate not merely between extremes of attitude but also among individual who differ slightly.

DIFFERENT SCALES FOR MEASURING ATTITUDES OF PEOPLE Name of the scale construction approach Name of the scales developed

2. Consensus scale approach Differential scales

(Thurstone Differential scale ) 3. Item analysis approach Summated ( Likert Scale ) 4. Cumulative scale approach Cumulative Scale

(Guttman’s Scalogram) 5. Factor analysis approach Factor scales

(Semantic differential, Multi-dimensional scaling) 1. Arbitrary Scale;

It is developed on ad hoc basis and are designed largely through the researcher’s own subjective selection of items. The researcher select few statement or item which he believes are appropriate to a given topic and it is include in measuring instrument.. Then people are asked to check in a list for their opinion.

Merits:

1. It is easy to develop quickly with less expense. 2. It can be designed highly specific and adequate

Demerits

1. It is not reliable

2. It rely on researcher’s insight and competence.

3. Differential scale (Thustone – type scale)

It is associated with differential scale which have been developed using consensus scale approach. In this selection is made by panel of judges

The procedure is

1. The researcher gather a large number of statements 2. The statements are submitted to panel of judges.

3. Each judge is request to arrange in position according to opinion.

4. Each judge is request to place the statement in first, second groups etc according to his favorableness.

5. In case of disagreement between the judges in assigning a position to an item that item is discarded.

6. A final selection of statements is then made .

7. The position of statements on the scale is determined by judges. Merits

1. It appropriate when we measure single attitude. 2. It is very reliable method

Demerits

1. It is costly method

2. Judge own attitude may reflect in arrangement 3. Summated Scale (Likert Scale)

It developed by utilizing the item analysis approach wherein in a particular item is evaluated on the basis of how well it discriminates between those persons whose total score is high and those whose score is low. Those items or statements that best meet this sort of discrimination test are included in the final instrument.

Procedure:

1. Researcher collect a number of statements relevant to the attitude being studied. 2. A trial test should be made with small group of people

3. The response to various statements are scored in such a way that a response of most favorable attitude is given the highest score of 5, and the most unfavorable attitude is given the lowest score of 1.

4. Then the total score of each respondent is obtained by adding his scores for separate statements.

5. Then arrange these scores & find out with those statements which have a high discriminating power. This way we determine which statement consistently co relate with high favorability & which with low favorability.

6. Only those statements that correlate with total test, should be retained in the final statement. And others must be removed.

Merits:

1. it is easy to construct in comparison to differential scale. 2. It is more reliable.

3. Each statement in this is given a test for discriminating ability, so it permits the use of only those statements that have direct relationship to the attitude being studied.

4. We can study how responses differ between people & how response differ between stimuli.

5. It takes less time to construct. Demerits:

1. In this method we can examine whether respondents are more or less favorable to the topic, but we can’t tell how much or less they are.

2. The interval between strongly agree & agree may not be equal to the interval between agree & undecided.

3. Often the total score of an individual respondent has little clear meaning since the given score can be secured by a variety of answer pattern.

4. Cumulative scale or scalogram:

It consists of a series of statements to which a respondents expresses his agreement or disagreement. The special feature of this scale is that statements in it form a cumulative series. The individual score is worked out by counting the number of points concerning number of statement he answered favorably. The major scale of this type of cumulative scales is the gutt man’s scalogram. The scalogram refers to the procedure for determining whether a set of items form a unidimensional scale. A scale is said to be unidimensional if response fall into a pattern in extreme and also less extreme points. Procedure;

1. The layout in clear terms the issue we want to deal in our study.

2. Develop a number of items relating the issue and to eliminate by inspection the items that are irrelevant or those that happen to be extreme items.

3. Pre-test the items whether the issue at hand is scalable. The respondent are asked to record their opinion on all items ranging from ‘strongly agree to strongly disagree. The score like 5 -1 was assigned. If there is 5 items in all, total, score can be from 75- 15. 4. Respondent opinionnaires are then arrayed according to total score for analysis and evaluation. If the responses of an item form a cumulative scale, its response category scores should decrease in an orderly fashion. After analyzing the preset results, a few items may be chosen.