Business Research Methods Notes

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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 existingknowledge. It is mainly concerned with generalization and formulation of theories.

Gathering knowledge for knowledges 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.

2. Quantitative Vs Qualitative research :

Department of Management Studies Jeppiaar Engineering College


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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 providesthe 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



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programmes, testing new products and product concepts and testing any variable

in a firms 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 subjects

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


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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.



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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 shouldselect 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.



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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



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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 sideand 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.



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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 toguide 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 hesucceeds 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.

Testable :



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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.



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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.

4. Selecting a random sample and computing an appropriate value :



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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.



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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.



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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 quantitativecharacteristic.

2. Make the variable like properties explicit by stating all of the variables

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.



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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

researchs 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 anddimension 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.



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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 samplefrom 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 in the desired type of study with useful conclusions



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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 withresearch 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 analysts interest in the problems.

To explain basic concepts.

While applying this design three different methods are followed.

Survey Of related Literature:



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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



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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 :

1. The laboratory experiment is artificial



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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 experimenters 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 experimenters 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



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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.



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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.

c) Treatment Vs Selection



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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.

g) Diffusion Of treatment



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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 thevariables 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 :



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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 , knownas 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


ExperimentalGroup

Level of [X]Performance

TrainingIntroduced

Level of [Y]Performance


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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


ExperimentalGroup Training

Introduced

Level of performanceafter training [Y]

ExperimentalGroup No Training

Level of performanceafter training [Z]

ExperimentalGroup

Level of Performance

[X]

Training Introduced

Level of Performance [Y]

Control Group

Level of Performance

[A]

No Training

Level of Performance [Z]


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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 RandomlySelected

Sample RandomlyAssigned

Treatment [A]

Control GroupTreatment [B]

ExperimentalGroup


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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

Random Selection

Sample

Random assignment

Population

Random Selection

Sample

Random assignment

Treatment A

Independent Variable (or) Casual Variable

Treatment B


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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 berandomly 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.QA

Very Low

I.QB

Very Low

I.QC

Very Low

I.QD

Very Low

I.QE

Form 1Form 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



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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



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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 19.4Level II 35.8 30.2 33.0Column Mean 256 26.7

Training

Control

Intelligence

Treatment A Treatment B Row Mean

Level I 10.4 20.6 15.5Level II 30.6 40.4 35.5Column Mean 20.5 80.5

b) Complex Factorial design:


40 BA

30

20

10

A B


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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 VariableTreatment A Treatment BC.V. 2

Level 1

C.V. 2

Level 2

C.V. 2

Level 1

C.V. 2

Level 2Control

Variable

Level ILevel 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.

1) Numbers are ordered



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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



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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.

b) Equivalence



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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.



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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 respondents 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 oneach 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.

j) Graphic rating scale:



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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

1. Arbitrary approach Arbitrary scales



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2. Consensus scale approach Differential scales(Thurstone Differential scale )

3. Item analysis approach Summated ( Likert Scale )

4. Cumulative scale approach Cumulative Scale

(Guttmans 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 researchers

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 researchers 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.



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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 isevaluated 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.



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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 cant 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 mans 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.



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5. Then total scores for the various opininnoires and to rearray them to reflect any shift in

order resulting from reducing the items.

Merits;

1. It assures that only a single dimension of attitude is measured.

2. Researchers subjective judgment is not allowed to creep in the development of

scale since the scale is determined by the replies of respondent.

3. It can be appropriately be used for personal, telephone or mail surveys.

Demerits:

1. It is very tedious & complex in preparation.

2. Conceptually is more difficult in comparison to other scaling methods.

3. It very a reliable source for assessing attitudes of persons towards complex objects.

5. Factor Scales:

It is developed on the basis of intercorrelations of items which indicate the degree

of interdependence. It include a variety of technique that have been developed for two

problem.

1) How to deal with the universe of content that is multidimensional.

2) How to uncover underlying dimension that have not been identified.

An important factor scale is semantic differential and multidimensional scaling.

a) Semantic differential scale :

It is an attempt to measure the psychological meanings of an object to an

individual.

b) Multidimensional scaling

It is characterized as a set of procedures for portraying perceptual or affective

dimension of substantive interest. It is used when all the variables are to be analysed are

happened to be independent. Through MDS techniques one can represent geometrically

the locations and interrelationship among a set of points.

Merits:

1. It is used in psychological survey.



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2. It is used to measure the perceptual structure of a set of stimuli and cognitive

processes underlying the development of this structure.

3. It is an important measurement tool for attitude.

Demerits:

1. It is complicated in calculation.

It is laborious in collection of data & analysis.

GENERAL GUIDELINES FOR DEVELOPING A MULTIPLE ITEM SCALE

Determine clearly what it is that you want to measure:

The scale should be well grounded in theory. The construct to be measured and

the scale itself should be specific. The construct should be clearly distinguishable

from other construct.

Generate as many items as possible:

Items essentially are statements that are relevant of the construct. The greater the

number of initial items generated. The better the final scale will be. The items that are

developed should not be too long nor should they pose any reading difficulty to the

respondent.

Ask expert to evaluate the initial pool of items:


Determine Clearly What You Are Going

To Measure

General As Many Items AsPossible

Ask Expert In The Field To EvaluateThe Initial Pool Of Items

Determine The Type Of AttitudinalScale To Be Used

Include Some Items That Will Help InThe Validation Of The Scale

Administer The Items To An InitialSample

Evaluate And Redefine The Items

Finally Optimize The Scale Length


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Experts are people who have worked one are currently working on the

phenomenon that is being studied. They can give inputs on the relevancy clarity and

conciseness of the items. Based on the experts evaluation the initial pool of items is

modified.

Determine the type of attitudinal scale to be used

The various scales such as the likert scale, semantic differential scale, Thurston

and associative scale has already been discussed should be selected. The type of

attitudinal scale to be used has to be decided quite early, because the wording of the

items varies with each scale format.

Include validation item in the scale:

Certain items are added to the scale in order to improve the scales validity and

also to detect certain flaw in it.

Administer the item to an initial sample:

Once it has been determined which construct related items are to be included in

the scale, the next step is to administer the scale to an initial sample. This is done to

check the validity of the items.

Evaluate and refine the item of the scale:

The ultimate quality that is sought in an item is high conctation with the true score

of the latent variable that is being measured. The properties that the items of a scale

should possess are high interconctation, high item scale conctation high item

variance, a mean close to the center of ht range of possible scores, and a high

coefficient alpha.

Optimize scale length:

The larger the scale, the greater the reliability but shorter scales are easier he

respondent to answer. Hence balance has to be struck between briefly and reliabilityand the optimal scale length have to be determined.

SAMPLING DESIGN

Population

A population is an identifiable total group of aggregation of elements.



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For Example: People, Products, Organizations, Physical Entities that are of

interest to the researcher and pertinent to the specified information problem.

Element:

An element is a person or object from which data and information are sought.

Sampling units:

Are the target population elements available for selection during the sampling

process.

Sampling frame:

After defining the target Population the researcher must assemble a list of all

eligible sampling units, referred to as a sampling frame.

Characteristic of a good sample design

1. Goal orientation:

The sample design should be oriented to the research objectives, tailored to the

survey design, and filtered to the survey conditions.

2. Measurability:

A sample design should enable the computation of valid estimates of its sampling

variability normally this variability is expressed in the form of standard errors in surveys.

3. Practicality:This implies that the sample design can be followed properly in the survey as it

also refers to simplicity of the design.

4. Economy:

It implies that the objectives of the survey should be achieved with minimum cost

and effort.

ADVANTAGES OF SAMPLING:

1. Sampling is cheaper than a census survey. It is obviously more economical for

instance to cover a sample of household than the entire household in a territory

although the cost per unit of study may be higher in a sample survey than in a

census survey.



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2. Since magnitude of operation involved in a sample survey is small, both the

execution of the fieldwork and the analysis of the results can be carried out

speedily.

3. Sampling results in greater economy of effort, as a relatively small staff is

required to carry out the survey and to tabulate and process the survey data.

4. A sample survey enables the researcher to collect more detailed information than

would otherwise be possible in a census survey. Also information of a more

specialized type can be collected which would not be possible in census survey on

account of the availability of a small number of specialist.

5. Since the scale of operation involved in a sample survey is small. The quantity of

the interviewing supervision and other related activities could be better than the

quality in a census survey.

LIMITATIONS OF SAMPLING:

1. When the information is needed on every unit in the population such as

individual, dwelling units a business establishment a sample survey cannot be of

much help for it fails to provide information on individual count.

2. Sampling gives rise to certain errors of these errors are too large, the results of the

sample survey will be of extremely limited use.

3. While in a census survey it may be easy to check the omissions of certain units in

view of complete coverage this is not so in the case of a sample survey.

UNIT III

DATA COLLECTION



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managers, public relation personnel and advertising personnel etc.

C. Miscellaneous

Company history

Company background

Market share

Pamplet

Prospectus

Annual General Body Meeting Report.

Organization manual, chart.

Organisation report.

External Sources i) Publication of (Government)

a. Reserve Bank of India Bulleting

b. Census Report

c. Registrar general of India

d. Central Statistical organization

e. Director general of commercial intelligence

f. Minisry of commerce & industry

g. Economic Advisor Office

h. Ministry of Agriculture

i. Labour Bureau.

ii) Non-government Publication

a. Private agencies

b. Stock exchange directories

c. Chamber of commerce

d. Federation of Indian Chamber of Commercee. Associate Chamber of commerce & Industry Of India

f. Indo- Amercian Chamber of Commerce etc

g. Promotion

h. Market Research & Statistical Bureau



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iii) Syndicated Services

These are provided provided by certain organization which collect

and tabulate marketing information on a continuing basis. Report based on the marketing

information collected by such organization is sent periodically to clients who are

subscribers. Apart from syndicated services a number of research agencies, offer and

customized research services to their clients.

iv) Technical and trade journals

v) Books, magazines & newspapers

vi) Reports prepared by research scholars universities economists etc in diff fields

vii) Public records and statistics, historical documents and other sources of published

information

viii) Various publications of foreign government or of international bodies and their subsidiary organizations.

CHARACTERISTCS OF SECONDARY DATA

1. Reliability of Data :

The reliability can be treated by finding out such things about the said data

a. Who collected the data?

b. What were the sources of data?

c. Were they collected by using proper methods?

d. At what time were they collected?

e. Was there any bias of the compiler?

f. What level of accuracy was desired?

2. Suitability of Data

The data that are suitable for one enquiry may not necessarily be

found suitable for one enquiry may not necessarily be found suitable in another

enquiry. Hence if the available data are found to be unsuitable. The researcher should not use them.

3. Adequacy of Data



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If the level of accuracy achieved in data is found inadequate for the purpose

of the present enquiry they will be considered as inadequate and should not used by

the researcher. The data will also be considered adequate.

4. Continuity of DataThis is another problem in using secondary data. For eg, the format used for

providing some date may not be consistently followed by the source. Depending upon

the page constraints or availability of material the data presentaion in a format is

decided. So frequent change in the format would only add to confusion to the people

using the data from such sources.

SPECIAL SOURCES

Computer Search & Internet Applications

Generally most databases allow the researcher to undertake precise searches using

combination of key words in the website.

1. Scanning & Browsing :

New publications such as journals are unlikely to be indexed immediately in

tertiary literature so you will need to browse through these publications to gain an

idea of their content. In contrast scanning involves going through individual items

such as journal articles to pick out points that are related to your own research.

2. Searching the Internet

The Internet is a worldwide network of computers that provides access to a

vast range of literature and other resources stored on computer around the world.

Searching these will uncover further material with which you can compare and

contrast your ides. The places where these resources are stored are known as

websites.

3. Home Page

Access to a website is through its home page. The home page, which has

links to other pages in the site, is similar to a title or contents page. Although they

often contain publicity for a company or institution they are an excellent way of

navigating the site.



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4. Search Tools:

It often referred to as search engines, are probably the most important way of

searching the internet for reviewing the literature on your research subject as they

enable you to locate the most current and up to date items.

5. Book marking

Once you have found a useful internet site, you will need to note its address.

This process termed bookmarking uses the internet browser to note the address so

that you will be able to access it again directly.

Sources of Primary Data

Advantages :-

1. It provide a first hand account of the situation. We can observe the phenomenon

as it takes place.

2. The information is more reliable as the investigator collects the data himself, he

can take all precautions to ensure their reliability

3. These are the logical starting point for research in several disciplines.

4. Primary data are the only way of finding out opinions, personal qualities, attitudes

etc. Disadvantages :-

1. Collecting primay data is expensive in terms of both time & money.

2. There is greater scope for researcher bias creeping in unless the research

investigator is fair to the respondent and methods of data collection the result of

the study will not be reliable.

3. Sample selection is yet another problem.

METHODS OF COLLECTING PRIMARY DATA

1. Questionnaire :-

In this method to pre-printed list of questions arranged in sequence is used to

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