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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 :
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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
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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
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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
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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
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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
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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:
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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:
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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