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BUSINESS RESEARCH
METHODS
ROSHAN.S
MB
A- J
RESEARCH
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Research can be defined as the scientific search for knowledge,
or as any systematic investigation, to establish novel facts,
solve new or existing problems, prove new ideas, or develop
new theories, usually using a scientific method.
In the broadest sense of the word, the definition of research
includes any gathering of data, information and facts for the
advancement of knowledge.
Research is an organized and systematic way of finding answers
to questions.
The research provides the needed information that guides
managers to make informed decisions to successfully deal with
problems.
BUSINESS RESEARCH:
It is a systematic inquiry that provides information to guide
managerial decisions.
It is a process of planning, acquiring, analyzing and
disseminating relevant data and information and insights to
decision makers in ways that mobilize the organization to take
appropriate actions that, in turn, maximize business
performance.
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Business research is a systematic and organized effort to
investigate a specific problem encountered in the work setting
that needs a solution.
Business research is an important management activity that
helps companies determine which products will be most
profitable for companies to produce.
Several steps are necessary when conducting business research;
each step must be thoroughly reviewed to ensure that the best
decision is made for the company.
TYPES OF RESEARCH
Research can be classified by purpose or by method.
If we categorise it by purpose, it would fall into two major
categories:
Basic Research and
Applied Research,
while in case of method, it would be
Deductive research and
Inductive research.
BASIC RESEARCH
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Also called Pure or fundamental Research, it is undertaken for
increase in knowledge.
There is no direct benefit as it is a research for the sake of
research.
It is conducted to satisfy any curiosity such as:
(a) What makes things happen,
(b) Why society changes and
(c) Why social relations are in a certain way.
In fact, it is the source of most new theories, principles and
ideas. Basic research rarely helps anyone directly.
It only stimulates new ways of thinking. The main motivation is
to expand man's knowledge.
There is absolutely no commercial value to the discoveries
resulting from such research.
To sum up, basic research is purely theoretical to increase our
understanding of certain phenomena or behaviour but does not
seek to solve any existing problem.
APPLIED RESEARACH
It is use of basic research or past theories, knowledge and
methods for solving an existing problem. It deals with practical
problems.
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It is opposed to pure research which is not problem-oriented but
for the increase in knowledge which may or may not be used in
future.
In the present world situation, more emphasis is being given to
applied research to solve problems arising out of overpopulation
and scarcity of natural resources.
Applied research should not be treated the same as Research &
Development (R&D) which is involved in developing products
demanded by the existing clients.
Applied Research, on the other hand, focuses on uncovering
what needs are not being met and use that information in
designing products or services that would create their own
demand.
Thus, applied research brings in new customers and also
provides better products and services to the existing customers.
In old days, the mobile phone was expensive, bulky and had a
short range.
Applied Research foresaw that this product would have a limited
market and stressed on cost-cutting, reduced weight and long-
distance communication. Such measures caused a heavy
demand.
METHODS or APPROACHES
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In research, conclusions are based two methods known as the
deduction and induction. Both are widely used in research
projects. This helps the researchers to understand, explain, or
predict business phenomena.
Deduction follows an approach which is top-down or from
general to specific. On the other hand, induction is bottom-
up in nature or from specific to general.
In deduction, we start from a theory and try to prove it right
with the help of available information. In induction, we observe
some happening, deduct a pattern and draw conclusion.
EXAMPLE OF DEDUCTION
All men are mortal. (General and no specific to one man)
Socrates is a man
(Therefore,) Socrates is mortal ( specific)
EXAMPLE OF INDUCTION
This ice is cold. (Specific, based on a direct observation.)
All ice is cold. (General, can be applied to any ice)
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Take another example: 3 + 5 = 8 and eight is an even
number. Therefore, an odd number added to another odd
number will result in an even number.
EXAMPLE OF BOTH DEDUCTION AND INDUCTION
1.You push the light switch and find no light
2.You ask the question, Why no light? (induction)
3.You infer a conclusion (hypotheses) to answer the question and
explain the fact that the bulb is burned out. (deduction)
4.You use this hypothesis to conclude (deduce) that the light will
not go on when we push the switch. We know from experience
that burned-out bulb will not light.
DEDUCTIVE METHOD
INDUCTIVE METHOD
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PROBLEM DEFINITION:
Problem definition is the crucial first stage in the research
process- determining the problems to be solved and the objectives
of the research.
THE PROCESS OF PROBLEM DEFINITION:
1. Ascertain the decision maker's objectives
2. Understand the background of the problem
3. Isolate the identify the problem rather than its symptoms
4. determine the unit of analysis
5. determine the relevant variables
6. State the research question (hypotheses) and research
objectives.
1. ICEBERG PRINCIPLE:
Is the idea that the dangerous part of many business problems
is neither visible to nor understood by business managers.
2. SITUATION ANALYSIS
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Is a preliminary investigation or informal gathering of
background information to familiarize researchers or managers
with the decision area.
3. VARIABLE
Is defined as anything that changes in value: anything that
assumes different numerical or categorical value.
CATEGORICAL VARIABLE
Is any variable that has a limited number of distinct values.
CONTINUOUS VARIABLE
Is any variable that has an infinitive number of possible values.
DEPENDENT VARIABLE
Is a criterion or a variable that is to be predicted or explained.
Independent variable is a variable that is expected to influence
the dependent variable. Its value may be changed
independently of any other variable.
4. RESEARCH OBJECTIVE
Is the purpose of the research, expressed in measurable terms; the
definition of what the research should accomplish.
5. RESEARCH PROPOSAL
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Is the written statement of the research design that includes a
statement explaining the purpose of the study and a detailed,
systematic outline of a particular research methodology.
THE NEED FOR THEORETICAL FRAMEWORK
A Theoretical Framework is a conceptual model of how one
theorizes or makes logical sense of the relationships among the
several factors that have been identified as important to the
problem.
It discusses the interrelationships among the variables that are
deemed to be integral to the dynamics of the situation being
investigated.
From the theoretical framework then, testable hypotheses can
be developed to examine whether the theory formulated is valid
or not.
THE MAIN DIFFERENTIATING FACTORS BETWEEN INTERNAL ANDEXTERNAL CONSULTANTS ARE SUMMARISED BELOW:
External InternalCredibility through brand status and
previous experienceCredibility through historyof interactions within the
businessBroad business perspective
bringing new ideasDeep organisational
perspectiveLimited organisation-specific
knowledge, possibly at content levelonly Not made here
Understands its culture,language and deeper
symbolic actionsPerceived as objective Perceived as an
organisational agentSpecial The same
Low investment in final success High investment in finalsuccess
Meets clients agenda Meets corporate agenda
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which may not be clientsNeeds time to understand the people
may misinterpret actions andinterpersonal dynamics
Knows the people, but mayhave preconceptions
On the clock timed, expensive,
rare and rationed
Free, accessible, and
available
VARIABLES
A variable is anything that can take on differing or varying
values. The values can differ at various times for the same
object or person, or at the same time for different objects or
persons.
Examples: Production, Motivation, Absenteeism
DEPENDENT VARIABLE
The dependent variable is the variable of primary interest to the
researcher.
DEPENDENT
INDEPENDENT
MODERATING
INTERVENING
TYPES OF
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The researcher goal is to describe and understand the
dependent variable or to explain its viability or predict it.
Through the analysis of the dependent variable it is possible to
find solutions to the problems. Researcher not only quantifies
and measures the dependent variable but explains other
variables that influence this variable.
Examples: Manager is interested in analyzing:
Debt-Equity Ratio.
Sales is not picking up
INDEPENDENT VARIABLE
An independent variable is one that influences the dependent
variable in either positive or negative way. When the
independent variable is present, the dependent variable is also
present, and with each unit of increase in the dependent
variable there is an increase or decrease in the dependent
variable also
MODERATING VARIABLE
The moderating variable is one that has a strong contingent
effect on the independent variable dependent variable
relationship.
INTERVENING VARIABLE
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An intervening variable is one that surfaces between the time
the independent variables start operating to influence the
dependent variable and the time their impact is felt on it.
Thus there is a temporal quality or time dimension to the
intervening variable. Explains the influence of the independent
variable on the dependent variable
THEORETICAL FRAMEWORK
The Theoretical Framework is the foundation on which the entire
research project is based.
It is logically developed, described and elaborated network of
associations among the variables deemed relevant to the
problem situation and identified through such processes as
interviews, observations and literature survey.
Experience and intuition also guide in developing the theoretical
framework.
Identify the problem first.
Identify the variables that contribute to it.
The purpose of interviews and literature review now becomes
clear.
Elaborate the network of associations among the variables.
So that the hypotheses can be developed and subsequently
tested.
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THE COMPONENTS OF THE THEORETICAL FRAMEWORK
1. The variables considered relevant to the study should be clearly
identified and labelled in the discussion.
2. The discussions should state how two or more variables are
related to one another. This should be done for the important
relationships that are theorized to exist among the variables.
3. If the nature and direction of the relationships can be theorized
on the basis of the findings of previous research, then there
should be an indication in the discussions as to whether the
relationships would be positive or negative.
4. There should be a clear explanation of why we would expect
these relationships to exist. The arguments could be drawn
from the previous research findings.5.
5. A schematic diagram of the theoretical framework should be
given so that the reader can see and easily comprehend the
theorized relationships.
HYPOTHESES DEVELOPMENT
Hypotheses can be defined as a logically conjectured
relationship between two or more variables expressed in the
form of attest able statement.
STATEMENT OF HYPOTHESES: FORMATS
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If Then Statements
Directional and Non-Directional Hypotheses
Null and Alternate Hypotheses
TYPES OF HYPOTHESES
1. DESCRIPTIVE HYPOTHESES
Describes the existence, size, form or distribution of some
variable.
60% of investors favours cash dividend.
MBA institutes facing problems in placement
2. RELATIONAL HYPOTHESES
Describes the relationship between two or more variables.
The greater the stress experienced in the job the lower the job-
satisfaction.( directional) Women are better than men
There is a relationship between age and job-satisfaction. (Non-
directional)
CORRELATIONAL HYPOTHESES
Only shows the correlation between two or more variables but
no claims are made that one causes the other.
EXPLANATORY HYPOTHESES.
Claims are made that one variable causes other to occur.
3. NULL HYPOTHESES
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The definitive statement that explains the relationship.
The null hypothesis relates to the statement being tested,
4. ALTERNATE HYPOTHESES
All other permissible relationship refers to alternative
hypothesis
The alternative hypothesis relates to the statement to be
accepted if / when the null hypothesis is rejected.
IMPORTANCE OF HYPOTHESES
Guides the direction of study;
Identifies the facts relevant for the study;
Helps in the selection of Research Design;
Helps in providing the framework in which the results have to
be given.
CHARACTERISTICS OF A GOOD HYPOTHESIS
1. ADEQUATE FOR THE PURPOSE
Should address the original problem
Clearly identifies the variables relevant in the study.
Helps in knowing the research design
Helps in organizing the results of the study
2. TESTABLE
Uses acceptable techniques
Simple requiring few conditions
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Explanation can be given from the given theoretical
framework.
3. BETTER THAN ITS RIVALS
Explains more facts than its rivals
Greater variety or scope of facts
RESEARCH DESIGN:
A research design is the arrangement of conditions for collection
and analysis of data in a manner that aims to combine relevance
to the research purpose with economy in procedure.
"A research design is the determination and statement of the
general research approach or strategy adopted/or the particular
project. It is the heart of planning. If the design adheres to the
research objective, it will ensure that the client's needs will be
served."
"Research design in the plan, structure and strategy of
investigation conceived so as to obtain answers to research
questions and to control variance."
"A research design is the specification of methods and
procedures for acquiring the information needed. It is the over-
all operational pattern or framework of the project that
stipulates what information is to be collected from which source
by what procedures."
NEED FOR RESEARCH DESIGN
Minimizes time and money
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Advance planning
Avoid flaws
Selection of appropriate tools
Eliminate bias and marginal error
FEATURES OF GOOD DESIGN
It should be flexible, appropriate, efficient, and economical and
so on.
It should give a smallest experimental error and high reliability
and validity.
Good research design includes following five important
elements.
Subjects
Variables
Time
Setting
Investigators role
PRINCIPLES OF RESEARCH DESIGN
1. PRINCIPLE OF REPLICATION
According to this principle, the experiment should be repeated
more than once. Thus, each treatment is applied in many
experimental units instead of one.
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By doing this method, the accuracy and precision of the study
are increased significantly. For example, the effect of two
variety of rice.
2. PRINCIPLE OF RANDOMIZATION
This principle provides protection
This principle indicates that the researcher 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. Example : effect of two variety of rice
3. PRINCIPLE OF LOCAL CONTROL
The extraneous factors, the know source of variability, is made
to vary deliberately over as wide a range as necessary and this
needs to be done in such a way that the variability it causes can
be measured and hence eliminated from the experimental error.
Example : effect of two variety of rice.
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TYPES OF RESEARCH DESIGN:
Quantitative Research Designs
Descriptive
Describe phenomena as they exist. Descriptive studiesgenerally take raw data and summarize it in a useableform.
Can also be qualitative in nature if the sample size issmall and data are collected from questionnaires,interviews or observations.
Experimental
The art of planning and implementing an experiment inwhich the research has control over some of the conditionswhere the study takes place and control over someaspects of the independent variable(s) (presumed cause orvariable used to predict another variable)
Quasi-experimen
tal
A form of experimental research. One in which theresearcher cannot control at least one of the three
elements of an experimental design:
Environment Intervention (program or practice)
Assignment to experimental and control groups
Qualitative Research Designs
Historical Collection and evaluation of data related to past eventsthat are used to describe causes, effects and trends thatmay explain present or future events. Data are often
archival.
Data includes interviews.
Ethnographic
The collection of extensive narrative data over anextended period of time in natural settings to gaininsights about other types of research.
Data are collected through observations at particularpoints of time over a sustained period.
Data include observations, records and interpretations of
what is seen.
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CaseStudies
An in-depth study of an individual group, institution,organization or program.
Data include interviews, field notes of observations,archival data and biographical data.
TYPES OF RESEARCH DESIGN
1. EXPLORATORY RESEARCH
Exploratory research is conducted to clarify ambiguous
problems. Management may have discovered general problems,
but research is needed to gain better understanding of the
dimensions of the problems.
Exploratory studies provide information to use in analyzing a
situation, but uncovering conclusive evidence to determine a
particular course of action is not the purpose of exploratory
research.
Usually, exploratory research is conducted with the expectation
that subsequent research will be required to provide conclusive
evidence, it is a serious mistake to rush into detailed surveys
before less expensive and more readily available sources of
information have been exhausted.
In an organisation considering a program to help employees
with childcare needs, for example, exploratory research with a
small number of employees who have children might determine
that many of them have spouses who also work and that these
employees have positive reactions to the possibility of an on-
site child-care program. In such a case exploratory research
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helps to crystallize a problem and identify information needs for
future research.
EXPLORATORY RESEARCH METHODS
The quickest and the cheapest way to formulate a hypothesis in
exploratory research is by using any of the four methods:
Literature search
Experience survey
Focus group
Analysis of selected cases
A. LITERATURE SEARCH
This refers to "referring to a literature to develop a new
hypothesis". The literature referred are - trade journals,
professional journals, market research finding publications,
statistical publications etc.
Example: Suppose a problem is "Why are sales down?" This can
quickly be analyzed with the help of published data which
should indicate "whether the problem is an "industry problem"
or a "firm problem".
THREE POSSIBILITIES EXIST TO FORMULATE THE HYPOTHESIS.
1. The company's market share has declined but industry's figures
are normal.
2. The industry is declining and hence the company's market share
is also declining.
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3. The industry's share is going up but the company's share is
declining. If we accept the situation that our company's sales
are down despite the market showing an upward trend, then we
need to analyse the marketing mix variables.
Example 1: A TV manufacturing company feels that its market
share is declining whereas the overall television industry is
doing very well.
Example 2: Due to a trade embargo imposed by a country,
textiles exports are down and hence sales of a company making
garment for exports is on the decline. The above information
may be used to pinpoint the reason for declining sales.
B. EXPERIENCE SURVEY
In experience surveys, it is desirable to talk to persons who are
well informed in the area being investigated.
These people may be company executives or persons outside the
organisation. Here, no questionnaire is required.
The approach adopted in an experience survey should be highly
unstructured, so that the respondent can give divergent views.
Since the idea of using experience survey is to undertake problem
formulation, and not conclusion, probability sample need not be
used.
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Those who cannot speak freely should be excluded from the
sample.
EXAMPLE 1:
1) A group of housewives may be approached for their choice for a
"ready to cook product". .
2) A publisher might want to find out the reason for poor
circulation of newspaper introduced recently. He might meet (a)
Newspaper sellers (b) Public reading room (c) General public (d)
Business community; etc. These are experienced persons whose
knowledge researcher can use
Focus Group
Another widely used technique in exploratory research is the
focus group. In a focus group, a small number of individuals are
brought together to study and talk about some topic of interest.
The discussion is co-ordinated by a moderator. The group
usually is of 8-12persons. While selecting these persons, care
has to be taken to see that they should have a common
background and have similar experiences in buying.
This is required because there should not be a conflict among
the group members on the common issues that are being
discussed. During the discussion, future buying attitudes,
present buying opinion etc., are gathered.
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Most of the companies conducting the focus groups, first screen
the candidates to determine who will compose the particular
group.
Firms also take care to avoid groups, in which some of the
participants have their friends and relatives, because this leads
to a biased discussion.
Normally, a number of such groups are constituted and the final
conclusions of various groups are taken for formulating the
hypothesis.
Therefore, a key factor in focus group is to have similar groups.
Normally there are 4-5 groups.
Some of them may even have 6-8 groups. The guiding criterion
is to see whether the latter groups are generating additional
ideas or repeating the same with respect to the subject under
study.
When this shows a diminishing return from the group, the
discussions stopped. The typical focus group lasts for 1-30 hours
to 2 hours.
The moderator under the focus group has a key role. His job is
to guide the group to proceed in the right direction
C. ANALYSIS OF SELECTED CASES
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Analysing a selected case sometimes gives an insight into the
problem which is being researched. Case histories of companies
which have undergone a similar situation may be available.
These case studies are well suited to carry out exploratory
research. However, the result of investigation of case histories
arc always considered suggestive, rather than conclusive.
In case of preference to "ready to eat food", many case histories
may be available in the form of previous studies made by
competitors.
We must carefully examine the already published case studies
with regard to other variables such as price, advertisement,
changes in the taste, etc.
2. DESCRIPTIVE RESEARCH
Descriptive research is used to obtain information concerning
the current status of the phenomena to describe "what exists"
with respect to variables or conditions in a situation.
The methods involved range from the survey which describes
the status quo, the correlation study which investigates the
relationship between variables, to developmental studies which
seek to determine changes over time.
A. CASE STUDIES:
A research strategy that focuses on exploration of a complex
phenomenon and related context.
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Case study refers to the collection and presentation of detailed
information about a particular participant or small group,
frequently including the accounts of subjects themselves.
A form of qualitative descriptive research, the case study looks
intensely at an individual or small participant pool, drawing
conclusions only about that participant or group and only in that
specific context.
Researchers do not focus on the discovery of a universal,
generalizable truth, nor do they typically look for cause-effect
relationships; instead, emphasis is placed on exploration and
description.
TYPES OF CASE STUDIES
1. EXPLANATORY: Used to do causal investigations.
2. EXPLORATORY: A case study that is sometimes used as a
prelude to further, more in-depth research. This allows
researchers to gather more information before developing their
research questions and hypotheses.
3. DESCRIPTIVE: Involves starting with a descriptive theory. The
subjects are then observed and the information gathered is
compared to the pre-existing theory.
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4. INTRINSIC: A type of case study in which the researcher has a
personal interest in the case.
5. COLLECTIVE: Involves studying a group of individuals.
6. INSTRUMENTAL: Occurs when the individual or group allows
researchers to understand more than what is initially obvious to
observers.
B. OBSERVATIONAL RESEARCH
A method of data collection in which the situation of interest is
watched and the relevant facts, actions and behaviours are
recorded.
An observational study is a study in which a researcher simply
observes behaviour in a systematic manner without influencing
or interfering with the behaviour.
The researcher would record the behaviour that he or she
observes. There may be rating scales that the researcher would
use when observing the behaviour.
Observational studies can involve naturalistic observation or
laboratory observation.
Naturalistic observation would involve observing behaviours in
the natural environment. Laboratory observation involves
observing behaviours in a research laboratory.
C. SURVEY RESEARCH
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Structured questions to assess peoples beliefs, attitudes, and
self- reports of behaviour. If the researcher wishes to generalize
the responses to a population, it is important to have a
representative sample.
Surveys that rely on self-selection (respond if you are
interested) produce non-generalizable results.
Surveys also provide information for co relational research. One
can correlate responses to some questions (often demographic
questions) with responses to other questions (often attitudes or
reports of behaviour).
Survey question must be clear and unambiguous. Even if the
questions are unambiguous and non-leading, people may
display a social desirability bias and give positive or socially
acceptable and desirable answers.
SURVEY METHODS INCLUDE:
1. the interview or face-to-face method which is generally viewed
as the best method for obtaining a high rate of responses but is
also very costly;
2. phone surveys, which are less expensive but have a higher non-
response rate (which has probably increased with caller ID); and
3. Written or mail surveys, which are least expensive but have a
very high non-response rate. Follow-up messages can help
increase the response rate.
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D. ARCHIVAL RESEARCH
Analysis of pre-existing data or records. Archival research often
involves content analysis, a qualitative analysis of material.
For example, one would use content analysis to determine
whether there had been an increase in the frequency with which
women and minorities were mentioned in US history books
between 1920 and 2000.Some archival research is quasi-
experimental.
3. EXPERIMENTAL RESEARCH
Science revolves around experiments, and learning the best way
of conducting an experiment is crucial to obtaining useful and
valid results.
When scientists speak of experiments, in the strictest sense of
the word, they mean a true experiment, where the scientist
controls all of the factors and conditions. Real world
observations, and case studies, should be referred to as
observational research, rather than experiments.
For example, observing animals in the wild is not a true
experiment, because it does not isolate and manipulate an
independent variable.
With an experiment, the researcher is trying to learn something
new about the world, an explanation of why something
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happens. The experiment must maintain internal and external
validity, or the results will be useless.
CLASSIFICATION BASED ON TIME (DIMENSION 2)
1. The categories of the second dimension for classifying non
experimental research, which refer to time, are:
2. Cross-sectional research, in which data are collected at one
point in time, often in order to make comparisons across
different types of respondents or participants.
3. Prospective or longitudinal research, in which data are collected
on multiple occasions starting with the present and going into
the future for comparisons across time. Data are sometimes
collected on different groups over time in order to determine
subsequent differences on some other variable.
4. Retrospective research, in which the researcher looks back in
time using existing or available data to explain or explore an
existing occurrence. This backwards examination may be an
attempt to find potential explanations for current group
differences.
CASUAL VS CORRELATION:
The Concise Oxford Dictionary defines correlation as mutual
relation between two or more things and causation as
causing or producing an effect.
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If two variables are highly correlated it does not necessarily
mean that one causes the other. To simply say that a correlation
exists does not imply causation.
Correlation is when two or more things or events tend to occur
at about the same time and might be associated with each
other, but aren't necessarily connected by a cause/effect
relationship.
For example, sick people tend to have a runny nose and a sore
throat. These two variables correlate to each other in that they
tend to show up in the same patients. That doesn't mean runny
noses cause sore throats, or that sore throats cause runny
noses
WHAT IS CORRELATION RESEARCH?
In correlation research, researchers investigate possible
relationships among variables without trying to influence those
variables. Although correlation studies cannot determine the
causes of relationships, they can suggest them.
WHAT IS THE PURPOSE OF CORRELATION RESEARCH?
Correlation research is carried out for one of two basic
purposes-either to help explain important human behaviours or
to predict likely outcomes.
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WHAT IS CAUSAL-COMPARATIVE RESEARCH?
In Causal-Comparative research allows researchers to
investigate the possibility of a causal relationship among
variables that cannot, as in experimental research, be
manipulated.
Two groups that are different on a particular variable are
compared on another variable.
WHAT IS THE PURPOSE OF CAUSAL-COMPARATIVE RESEARCH?
In Causal-Comparative research, investigators attempt to
determine the cause or consequences of differences that
already exist between or among groups of individuals
SIMILARITIES BETWEEN CAUSAL-COMPARATIVE AND CORRELATION
RESEARCH.
Both causal-comparative and correlation studies are examples
of associational research. Researchers who conduct both studies
seek to explore relationships among variables.
Both seek to identify variables that are worthy of later
exploration through experimental research, and both often
provide guidance for subsequent experimental studies.
DIFFERENCES BETWEEN CAUSAL-COMPARATIVE AND CORRELATION
RESEARCH.
Causal-comparative studies typically compare two or more
groups of subjects, while correlational studies require a score on
each variable for each subject.
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Correlational studies investigate two (or more) quantitative
variables, whereas causal-comparative studies involve at least
one categorical variable.
Correlational studies analyze data using scatter plots and/or
correlation coefficients, while causal-comparative studies
compare averages or use cross break tables.
In experimental research, the independent variable is
manipulated; in causal comparative research, no manipulation
takes places
DATA COLLECTION:
Data Collection is an important aspect of any type of research
study. Inaccurate data collection can impact the results of a
study and ultimately lead to invalid results.
Data collection methods for impact evaluation vary along a
continuum. At the one end of this continuum are quantitative
methods and at the other end of the continuum are Qualitative
methods for data collection.
QUANTITATIVE AND QUALITATIVE DATA COLLECTION METHODS
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THE QUANTITATIVE DATA COLLECTION METHODS rely on random
sampling and structured data collection instruments that fit
diverse experiences into predetermined response categories.
They produce results that are easy to summarize, compare, and
generalize.
Quantitative research is concerned with testing hypotheses
derived from theory and/or being able to estimate the size of a
phenomenon of interest.
Depending on the research question, participants may be
randomly assigned to different treatments. If this is not
feasible, the researcher may collect data on participant and
situational characteristics in order to statistically control for
their influence on the dependent, or outcome, variable.
If the intent is to generalize from the research participants to a
larger population, the researcher will employ probability
sampling to select participants.
TYPICAL QUANTITATIVE DATA GATHERING STRATEGIES INCLUDE:
EXPERIMENTS/CLINICAL TRIALS.
Observing and recording well-defined events (e.g., counting the
number of patients waiting in emergency at specified times of
the day). Obtaining relevant data from management information
systems.
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Administering surveys with closed-ended questions (e.g., face-
to face and telephone interviews, questionnaires etc.).
INTERVIEWS
In Quantitative research (survey research), interviews are more
structured than in Qualitative research.
In a structured interview, the researcher asks a standard set of
questions and nothing more.
A. FACE -TO -FACE INTERVIEWS
FACE -TO -FACE INTERVIEWS have a distinct advantage of
enabling the researcher to establish rapport with potential
participants and therefor gain their cooperation.
These interviews yield highest response rates in survey
research. They also allow the researcher to clarify ambiguous
answers and when appropriate, seek follow-up information.
Disadvantages include impractical when large samples are
involved time consuming and expensive.
B. TELEPHONE INTERVIEWS
Telephone interviews are less time consuming and less
expensive and the researcher has ready access to anyone on the
planet who has a telephone.
Disadvantages are that the response rate is not as high as the
face-to- face interview as but considerably higher than the
mailed questionnaire.
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The sample may be biased to the extent that people without
phones are part of the population about whom the researcher
wants to draw inferences.
C. COMPUTER ASSISTED PERSONAL INTERVIEWING
Computer Assisted Personal Interviewing (CAPI): is a form of
personal interviewing, but instead of completing a
questionnaire, the interviewer brings along a laptop or hand-
held computer to enter the information directly into the
database.
This method saves time involved in processing the data, as well
as saving the interviewer from carrying around hundreds of
questionnaires.
However, this type of data collection method can be expensive
to set up and requires that interviewers have computer and
typing skills.
QUESTIONNAIRES
Paper-pencil-questionnaires can be sent to a large number of
people and saves the researcher time and money.
People are more truthful while responding to the questionnaires
regarding controversial issues in particular due to the fact that
their responses are anonymous. But they also have drawbacks.
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Majority of the people who receive questionnaires don't return
them and those who do might not be representative of the
originally selected sample.
WEB BASED QUESTIONNAIRES:
A new and inevitably growing methodology is the use of Internet
based research.
This would mean receiving an e-mail on which you would click on
an address that would take you to a secure web-site to fill in a
questionnaire.
This type of research is often quicker and less detailed.
Some disadvantages of this method include the exclusion of
people who do not have a computer or are unable to access a
computer.
Also the validity of such surveys is in question as people might
be in a hurry to complete it and so might not give accurate
responses.
Questionnaires often make use of Checklist and rating scales.
These devices help simplify and quantify people's behaviours
and attitudes.
A checklist is a list of behaviours, characteristics, or other
entities that te researcher is looking for. Either the researcher
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or survey participant simply checks whether each item on the
list is observed, present or true or vice versa.
A rating scale is more useful when behaviour needs to be
evaluated on a continuum. They are also known as Likert scales.
QUALITATIVE DATA COLLECTION METHODS
Qualitative data collection methods play an important role in
impact evaluation by providing information useful to understand
the processes behind observed results and assess changes in
peoples perceptions of their well-being.
Furthermore qualitative methods can be used to improve the
quality of survey-based quantitative evaluations by helping
generate evaluation hypothesis; strengthening the design of
survey questionnaires and expanding or clarifying quantitative
evaluation findings.
THESE METHODS ARE CHARACTERIZED BY THE FOLLOWING
ATTRIBUTES:
they tend to be open-ended and have less structured protocols
(i.e., researchers may change the data collection strategy by
adding, refining, or dropping techniques or informants)
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they rely more heavily on interactive interviews; respondents
may be interviewed several times to follow up on a particular
issue, clarify concepts or check the reliability of data
they use triangulation to increase the credibility of their
findings (i.e., researchers rely on multiple data collection
methods to check the authenticity of their results)
generally their findings are not generalizable to any specific
population, rather each case study produces a single piece of
evidence that can be used to seek general patterns among
different studies of the same issue
Regardless of the kinds of data involved, data collection in a
qualitative study takes a great deal of time.
The researcher needs to record any potentially useful data
thoroughly, accurately, and systematically, using field notes,
sketches, audiotapes, photographs and other suitable means.
The data collection methods must observe the ethical principles
of research. The qualitative methods most commonly used in
evaluation can be classified in three broad categories:
IN-DEPTH INTERVIEW
OBSERVATION METHODS
DOCUMENT REVIEW
DIFFERENT DATA COLLECTION METHODS ARE GIVEN BELOW.
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BEHAVIOUR OBSERVATION CHECKLIST:
A list of behaviours or actions among participants being observed.
A tally is kept for each behaviour or action observed.
KNOWLEDGE TESTS:
Information about what a person already knows or has learned.
OPINION SURVEYS:
An assessment of how a person or group feels about a particular
issue.
PERFORMANCE TESTS:
Testing the ability to perform or master a particular skill.
DELPHI TECHNIQUE:
A method of survey research that requires surveying the same
group of respondents repeatedly on the same issue in order to
reach a consensus.
Q-SORTS:
A rank order procedure for sorting groups of objects. Participants
sort cards that represent a particular topic into different piles that
represent points along a continuum.
SELF-RATINGS:
A method used by participants to rank their own performance,
knowledge, or attitudes.
QUESTIONNAIRE:
A group of questions that people respond to verbally or in writing.
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TIME SERIES:
Measuring a single variable consistently over time, i.e. daily,
weekly, monthly, annually.
CASE STUDIES:
Experiences and characteristics of selected persons involved with
a project.
INDIVIDUAL INTERVIEWS:
Individuals responses, opinions, and views.
GROUP INTERVIEWS:
Small groups responses, opinions, and views.
WEAR AND TEAR:
Measuring the apparent wear or accumulation on physical objects,
such as a display or exhibit.
PHYSICAL EVIDENCE:
Residues or other physical by-products are observed.
PANELS, HEARINGS:
Opinions and ideas.
RECORDS:
Information from records, files, or receipts.
LOGS, JOURNALS:
A persons behaviour and reactions recorded as a narrative.
SIMULATIONS:
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A persons behaviour in simulated settings.
ADVISORY, ADVOCATE TEAMS:
Ideas and viewpoints of selected persons.
JUDICIAL REVIEW:
Evidence about activities is weighed and assessed by a jury of
professionals
PRIMARY DATA COLLECTION
Primary data collection is necessary when a researcher cannot
find the data needed in secondary sources.
Market researchers are interested in primary data about
demographic/socioeconomic characteristics,
attitudes/opinions/interests, awareness/knowledge, intentions,
motivation, and behaviour.
Three basic means of obtaining primary data are observation,
surveys, and experiments. The choice will be influenced by the
nature of the problem and by the availability of time and money.
Examples include surveys, interviews, observations, and
ethnographic research. A good researcher knows how to use
both primary and secondary sources in her writing and to
integrate them in a cohesive fashion. Conducting primary
research is a useful skill to acquire as it can greatly supplement
research in secondary sources, such as journals, magazines, or
books. Primary research is an excellent skill to learn as it can be
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useful in a variety of settings including business, personal, and
academic
TYPES OF PRIMARY RESEARCH:
Many types of primary research exist. This guide is designed to
provide you with an overview of primary research that is often
done in writing classes.
INTERVIEWS:
Interviews are one-on-one or small group question and answer
sessions.
Interviews will provide a lot of information from a small number
of people and are useful when you want to get an expert or
knowledgeable opinion on a subject.
SURVEYS:
Surveys are a form of questioning that is more rigid than
interviews and that involve larger groups of people. Surveys will
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provide a limited amount of information from a large group of
people and are useful when you want to learn what a larger
population thinks.
OBSERVATIONS:
Observations involve taking organized notes about occurrences
in the world. Observations provide your insight about specific
people, events, or locales and are useful when you want to learn
more about an event without the biased viewpoint of an
interview.
ANALYSIS:
Analysis involves collecting data and organizing it in some
fashion based on criteria you develop. They are useful when you
want to find some trend or pattern. A type of analysis would be
to record commercials on three major television networks and
analyze gender roles.
INTERVIEWING
Interviewing is a great way to learn detailed information from a
single individual or small number of individuals. It is very useful
when you want to gain expert opinions on the subject or talk to
someone knowledgeable about a topic.
TYPES OF INTERVIEWING:
Several different types of interviews exist. You should choose one
based on what kind of technology you have available to you, the
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availability of the individual you are interviewing, and how
comfortable you feel talking to people.
1. FACE TO FACE INTERVIEWS:
Face to face interviews are when you sit down and talk with
someone. They are beneficial because you can adapt your
questioning to the answers of the person you are interviewing.
You will need recording equipment for the interview, and it is
highly recommended that you bring two recording devices with
you in case one fails.
2. PHONE INTERVIEWS:
Phone interviews can be used when you need to interview
someone who is geographically far away, who is too busy to meet
with you to talk, or who does not want to use Internet technology.
You have to purchase a special recording device for use with most
phone systems.
3. EMAIL INTERVIEWS:
Email interviews are less personal than face-to-face or phone
interviews, but highly convenient for most individuals. You may
not get as much information from someone in an email interview
because you are not able to ask follow-up questions or play off the
interviewees responses. However, email interviews are useful
because they are already in a digital format.
4. CHAT/MESSAGING INTERVIEWS:
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It is also possible to interview someone via an instant messaging
service such as MSN Messenger, ICQ, or AOL Instant Messenger.
These interviews allow you to talk to people at great distances and
give you the benefit of adapting your questioning based on the
responses you receive. Some people are not fluent at typing,
however, so you may not get as lengthy responses from this
option
SECODARY SOURCES OF DATA:
Data from a secondary source is any data which has been
collected by another researcher, whether it is a group of people
or just one person.
The data may have originally been used for a different type of
research, but you can manipulate it to fit your research, instead
of using it as it was intended to be used. Here are some
examples of secondary sources of data for research:
GOVERNMENTAL STUDIES
If the government of your country has collected data on a
particular topic, you can manipulate this data in any way you
choose.
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For example, the government has records on the types of
benefits it awards each year, and how much money is spent on
benefits.
You could manipulate this data for any topic you wish to
research, for example, if you were doing a study surrounding
the unemployed people of your country.
LARGE COMPANIES
Large companies and manufacturers keep all kinds of data on
their products and business.
For example, computer and software manufacturers like Apple
and Microsoft will have records of how much of each of their
products has been bought in a particular year.
You could use data from two different companies in order to
compare them, or you could use data from one particular
company in order to do an in-depth analysis.
SCIENTIFIC STUDIES
You could manipulate data gathered by scientists as a result of
particular research they have carried out.
Teams of scientists are constantly undertaking research and
collecting and recording data as a result, which you could
manipulate into your research.
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However, scientific reports and results sheets are often difficult
to decipher, as they use a great deal of scientific jargon.
SAMPLING:
Sampling Method means selection of a limited number of items
representing the population or universe for studying the
characteristics of the whole population or universe.
Example: to know the IQ of the Students of age between 15-16,
suppose in the class of 70 students. We conduct the study on 20
students who represent the class.
Population = 70
Sample = 20
ESSENTIALS OF SAMPLING
Sample should possess same characteristics as the population.
Absolute accuracy is not essential.
Regulating conditions should be same for every individual item
in the sample
ADVANTAGES OF SAMPLING
The result obtained is generally more reliable than that
obtained from a complete count.
Total financial burden of a sample survey is generally less than
that of complete census.
Possible to collect more detailed information in a sample survey.
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Causes less damage and wastage.
DISADVANTAGES:
Shortage of experts in the sampling field is a serious hurdle in
the way of reliable statistics.
Sampling plan may be complicated that it requires more time,
labour and money than a complete count.
Must be carefully planned and executed otherwise the results
obtained may be inaccurate and misleading.
SAMPLING:
A Sampling is a part of the total population. It can be an
individual element or a group of elements selected from the
population.
Although it is a subset, it is representative of the population and
suitable for research in terms of cost, convenience, and time.
The sample group can be selected based on a probability or a
non-probability approach.
A sample usually consists of various units of the population. The
size of the sample is represented by n.
Sampling is the act, process, or technique of selecting a
representative part of a population for the purpose of
determining the characteristics of the whole population.
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In other words, the process of selecting a sample from a
population using special sampling techniques called sampling.
It should be ensured in the sampling process itself that the
sample selected is representative of the population.
POPULATION OR UNIVERSE:
The entire aggregation of items from which samples can be
drawn is known as a population. In sampling, the population
may refer to the units, from which the sample is drawn.
Population or populations of interest are interchangeable terms.
The term unit is used, as in a business research process;
samples are not necessarily people all the time.
A population of interest may be the universe of nations or cities.
This is one of the first things the analyst needs to define
properly while conducting a business research.
Therefore, population, contrary to its general notion as a
nations entire population has a much broader meaning in
sampling. N represents the size of the population.
CENSUS:
A complete study of all the elements present in the population is
known as a census.
It is a time consuming and costly process and is, therefore,
seldom a popular with researchers. The general notion that a
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census generates more accurate data than sampling is not
always true.
Limitations include failure in generating a complete and
accurate list of all the members of the population and refusal of
the elements to provide information. The national population
census is an example of census survey.
PRECISION:
Precision is a measure of how close an estimate is expected to
be, to the true value of a parameter.
Precision is a measure of similarity. Precision is usually
expressed in terms of imprecision and related to the standard
error of the estimate.
Less precision is reflected by a larger standard error.
BIAS:
Bias is the term refers to how far the average statistic lies from
the parameter it is estimating, that is, the error, which arises
when estimating a quantity.
Errors from chance will cancel each other out in the long run,
those from bias will not. Bias can take different forms.
STEPS IN SAMPLING PROCESS:
An operational sampling process can be divided into seven steps
as given below:
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1. Defining the target population.
2. Specifying the sampling frame.
3. Specifying the sampling unit.
4. Selection of the sampling method.
5. Determination of sample size.
6. Specifying the sampling plan.
7. Selecting the sample.
1. DEFINING THE TARGET POPULATION:
Defining the population of interest, for business research, is the
first step in sampling process. In general, target population is
defined in terms of element, sampling unit, extent, and time
frame.
The definition should be in line with the objectives of the
research study. For ex, if a kitchen appliances firm wants to
conduct a survey to ascertain the demand for its micro ovens, it
may define the population as all women above the age of 20
who cook (assuming that very few men cook).
However this definition is too broad and will include every
household in the country, in the population that is to be covered
by the survey.
Therefore the definition can be further refined and defined at
the sampling unit level, that, all women above the age 20, who
cook and whose monthly household income exceeds Rs.20,000.
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This reduces the target population size and makes the research
more focused. The population definition can be refined further
by specifying the area from where the researcher has to draw
his sample, that is, households located in Hyderabad.
A well-defined population reduces the probability of including
the respondents who do not fit the research objective of the
company.
For ex, if the population is defined as all women above the age
of 20, the researcher may end up taking the opinions of a large
number of women who cannot afford to buy a micro oven.
2. SPECIFYING THE SAMPLING FRAME:
Once the definition of the population is clear a researcher
should decide on the sampling frame.
A sampling frame is the list of elements from which the sample
may be drawn. Continuing with the micro oven ex, an ideal
sampling frame would be a database that contains all the
households that have a monthly income above Rs.20, 000.
However, in practice it is difficult to get an exhaustive sampling
frame that exactly fits the requirements of a particular research.
In general, researchers use easily available sampling frames like
telephone directories and lists of credit card and mobile phone
users. Various private players provide databases developed
along various demographic and economic variables.
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Sometimes, maps and aerial pictures are also used as sampling
frames. Whatever may be the case, an ideal sampling frame is
one that entire population and lists the names of its elements
only once.
A sampling frame error pops up when the sampling frame does
not accurately represent the total population or when some
elements of the population are missing another drawback in the
sampling frame is over representation.
A telephone directory can be over represented by
names/household that have two or more connections.
3. SPECIFYING THE SAMPLING UNIT:
A sampling unit is a basic unit that contains a single element or
a group of elements of the population to be sampled.
In this case, a household becomes a sampling unit and all
women above the age of 20 years living in that particular house
become the sampling elements.
If it is possible to identify the exact target audience of the
business research, every individual element would be a
sampling unit.
This would present a case of primary sampling unit. However, a
convenient and better means of sampling would be to select
households as the sampling unit and interview all females above
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20 years, who cook. This would present a case of secondary
sampling unit.
4. SELECTION OF THE SAMPLING METHOD:
The sampling method outlines the way in which the sample units
are to be selected.
The choice of the sampling method is influenced by the
objectives of the business research, availability of financial
resources, time constraints, and the nature of the problem to be
investigated.
All sampling methods can be grouped under two distinct heads,
that is, probability and non-probability sampling.
5. DETERMINATION OF SAMPLE SIZE:
The sample size plays a crucial role in the sampling process.
There are various ways of classifying the techniques used in
determining the sample size.
A couple those hold primary importance and are worth
mentioning are whether the technique deals with fixed or
sequential sampling and whether its logic is based on traditional
or Bayesian methods.
In non-probability sampling procedures, the allocation of
budget, thumb rules and number of sub groups to be analyzed,
importance of the decision, number of variables, nature of
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analysis, incidence rates, and completion rates play a major role
in sample size determination.
In the case of probability sampling, however, formulas are used
to calculate the sample size after the levels of acceptable error
and level of confidence are specified.
The details of the various techniques used to determine the
sample size will be explained at the end of the chapter.
6. SPECIFYING THE SAMPLING PLAN:
In this step, the specifications and decisions regarding the
implementation of the research process are outlined. Suppose,
blocks in a city are the sampling units and the households are
the sampling elements.
This step outlines the modus operandi of the sampling plan in
identifying houses based on specified characteristics. It includes
issues like how is the interviewer going to take a systematic
sample of the houses.
What should the interviewer do when a house is vacant? What is
the re contact procedure for respondents who were unavailable?
All these and many other questions need to be answered for the
smooth functioning of the research process.
These are guide lines that would help the researcher in every
step of the process.
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As the interviewers and their co-workers will be on field duty of
most of the time, a proper specification of the sampling plans
would make their work easy and they would not have to revert
to their seniors when faced with operational problems.
7. SELECTING THE SAMPLE:
This is the final step in the sampling process, where the actual
selection of the sample elements is carried out.
At this stage, it is necessary that the interviewers stick to the
rules outlined for the smooth implementation of the business
research.
This step involves implementing the sampling plan to select the
sampling plan to select a sample required for the survey.
TYPES OF SAMPLES
The best sampling is probability sampling, because it increases
the likelihood of obtaining samples that are representative of the
population.
PROBABILITY SAMPLING (REPRESENTATIVE SAMPLES)
Probability samples are selected in such a way as to be
representative of the population.
They provide the most valid or credible results because they
reflect the characteristics of the population from which they are
selected (e.g., residents of a particular community, students at
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an elementary school, etc.). There are two types of probability
samples: random and stratified.
RANDOM SAMPLE
The term random has a very precise meaning. Each individual in
the population of interest has an equal likelihood of selection.
This is a very strict meaning -- you can't just collect responses
on the street and have a random sample.
The assumption of an equal chance of selection means that
sources such as a telephone book or voter registration lists are
not adequate for providing a random sample of a community.
In both these cases there will be a number of residents whose
names are not listed. Telephone surveys get around this
problem by random-digit dialling -- but that assumes that
everyone in the population has a telephone.
The key to random selection is that there is no bias involved in
the selection of the sample. Any variation between the sample
characteristics and the population characteristics is only a
matter of chance.
STRATIFIED SAMPLE
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A stratified sample is a mini-reproduction of the population.
Before sampling, the population is divided into characteristics of
importance for the research.
For example, by gender, social class, education level, religion,
etc. Then the population is randomly sampled within each
category or stratum. If 38% of the population is college-
educated, then 38% of the sample is randomly selected from the
college-educated population.
Stratified samples are as good as or better than random
samples, but they require a fairly detailed advance knowledge
of the population characteristics, and therefore are more
difficult to construct.
NONPROBABILITY SAMPLES (NON-REPRESENTATIVE SAMPLES)
As they are not truly representative, non-probability samples
are less desirable than probability samples.
However, a researcher may not be able to obtain a random or
stratified sample, or it may be too expensive.
A researcher may not care about generalizing to a larger
population. The validity of non-probability samples can be
increased by trying to approximate random selection, and by
eliminating as many sources of bias as possible.
QUOTA SAMPLE
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The defining characteristic of a quota sample is that the
researcher deliberately sets the proportions of levels or strata
within the sample.
This is generally done to insure the inclusion of a particular
segment of the population.
The proportions may or may not differ dramatically from the
actual proportion in the population. The researcher sets a quota,
independent of population characteristics.
Example: A researcher is interested in the attitudes of members
of different religions towards the death penalty. In Iowa a
random sample might miss Muslims (because there are not
many in that state).
To be sure of their inclusion, a researcher could set a quota of
3% Muslim for the sample. However, the sample will no longer
be representative of the actual proportions in the population.
This may limit generalizing to the state population. But the
quota will guarantee that the views of Muslims are represented
in the survey.
PURPOSIVE SAMPLE
A purposive sample is a non-representative subset of some
larger population, and is constructed to serve a very specific
need or purpose. A researcher may have a specific group in
mind, such as high level business executives.
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It may not be possible to specify the population -- they would
not all be known, and access will be difficult. The researcher will
attempt to zero in on the target group, interviewing whoever is
available.
A subset of a purposive sample is a snowball sample -- so named
because one picks up the sample along the way, analogous to a
snowball accumulating snow.
A snowball sample is achieved by asking a participant to
suggest someone else who might be willing or appropriate for
the study.
Snowball samples are particularly useful in hard-to-track
populations, such as truants, drug users, etc.
CONVENIENCE SAMPLE
A convenience sample is a matter of taking what you can get. It
is an accidental sample.
Although selection may be unguided, it probably is not random,
using the correct definition of everyone in the population having
an equal chance of being selected. Volunteers would constitute
a convenience sample.
Non-probability samples are limited with regard to
generalization. Because they do not truly represent a
population, we cannot make valid inferences about the larger
group from which they are drawn.
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Validity can be increased by approximating random selection as
much as possible, and making every attempt to avoid
introducing bias into sample selection.
QUESTIONNAIR DESIGN:
Two important aspects of questionnaire design are the structure
of the questions and the decisions on the types of response
formats for each question. Broadly speaking, survey questions can
be classified into three structures: closed, open-ended, and
contingency questions.
CLOSED:
Closed (or multiple choice) questions ask the respondent to
choose, among a possible set of answers, the response that
most closely represents his/her viewpoint.
The respondent is usually asked to tick or circle the chosen
answer.
Questions of this kind may offer simple alternatives such as
Yes or No. They may also require that the respondent
chooses among several answer categories, or that he/she uses a
frequency scale, an importance scale, or an agreement scale.
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How often do your parents ask you about your homework?
(Please, circle one answer only)
Never . . . . . . . . . . . . . . . . . . 1
1 or 2 times a week . . . . . . . 2
3 or 4 times a week . . . . . . 3
Nearly every day . . . . . . . . 4
THE MAIN ADVANTAGE OF CLOSED QUESTIONS ARE:
The respondent is restricted to a finite (and therefore more
manageable) set of responses,
They are easy and quick to answer,
They have response categories that are easy to code, and
They permit the inclusion of more variables in a research study
because the format enables the respondent to answer more
questions in the same time required to answer fewer open-
ended questions.
THE MAIN DISADVANTAGES WITH CLOSED QUESTIONS ARE:
a. They can introduce bias, either by forcing the respondent to
choose between given alternatives or by offering alternatives
that otherwise would not have come to mind,
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b. They do not allow for creativity or for the respondent to develop
ideas,
c. They do not permit the respondent to qualify the chosen
response or express a more complex or subtle meaning,
d. They can introduce bias, where there is a tendency for the
respondent to tick systematically either the first or last
category, to select what may be considered as the most socially
desirable response alternative, or to answer all items in a list in
the same way, and
e. They require skill to write because response categories need to
be appropriate, and mutually exclusive.
The response format for closed questions can range from a
simple yes/no response, to an approve/disapprove alternative,
to asking the respondent to choose one alternative from 3 or
more response options.
The possibility of format effects or response bias for this type of
question can be reduced by changing the sequence of response
categories and values.
For example, if responses to an item range from 1 to 5, going
from negative to positive, then a number of items in the
questionnaire can be designed to have 1 as the most positive
alternative and 5 as the most negative. This is a particularly
important technique for the construction of attitude scales.
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Some closed questions may have a dichotomous response
format, which means only two mutually exclusive responses are
provided.
What is your sex?
(Please tick one box only)
o Male
o Female
For the above example a dichotomous response format is
appropriate. However, this type of format should not be
overused in a survey because it elicits much less information
than multiple choice formats.
For example, if seeking information on degree of interest in
public affairs, the question Do you read a daily newspaper?
yields a yes/no response. This could be reworded to:
How many times per week do you read a daily newspaper? to
which multiple choice responses could be:
1. Seven times a week
2. Five to six times a week
3. Three to four times a week
4. One to two times per week
5. Less than once per week
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6. Never
Such a multiple category response format would provide more
specific and more useful information than the dichotomous one.
OPED ENDED:
Open-ended or free-response questions are not followed by any
choices and the respondent must answer by supplying a
response, usually by entering a number, a word, or a short text.
Answers are recorded in full, either by the interviewer or, in the
case of a self-administered survey, the respondent records his
or her own entire response.
What are your favourite TV programmes?
(Please specify their titles)
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . .
What do you like most about school?
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . .
THE MAIN ADVANTAGES OF OPEN-ENDED QUESTIONS ARE:
a. They allow respondents to express their ideas spontaneously in
their own language,
b. They are less likely to suggest or guide the answer than closed
questions because they are free from the format effects
associated with closed questions, and
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c. They can add new information when there is very little existing
information available about a topic.
THE MAIN DISADVANTAGES OF OPEN-ENDED QUESTIONS ARE:
a. They may be difficult to answer and even more difficult to
analyze,
b. they require effort and time on behalf of the respondent,
c. They require the development of a system of coded categories
with which to classify the responses,
d. They require the respondent to have some degree of writing
ability, and
e. Respondent handwriting can be illegible.
There is always the possibility with open-ended questions that
responses may come in very different forms, and these may lead
to answers that cannot be systematically coded for analysis.
For example, if asked When did you leave school?, the
respondent may answer in a variety of ways: Seven years ago.
When I got my first job. When my brother started going to
high school. When my parents moved into this house.
If the survey is administered by an interviewer, appropriate
probing helps clarify such answers. In the case of a self-
administered survey, guidance by writing specific instructions
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on how to answer the question can often minimize the number
of responses that have very different dimensions.
Care should be taken in writing open-ended questions so as to
avoid formats that elicit a dichotomous yes/no or agree/disagree
response. In addition, the wording of questions should seek to
reduce the possibility of eliciting responses that are aligned
along very different dimensions and therefore cannot be
systematically coded.
For example, asking What do you think about your school?
can elicit responses such as nothing or school is useless.
However, asking What recommendations would you have for
improving your school? would be more likely to elicit
informative answers.
A good case for using open-ended questions is when the aim is
to have the respondents reply spontaneously, or when the
investigator is pilot testing the first version of the
questionnaire, or when the investigator wants to collect
evidence on the parameters of an issue with the aim of later
formulating a multiple choice or closed version of a question.
Generally, open-ended questions can produce useful information
in an interviewer administered survey, provided that the
interviewers are alert and trained to probe ambiguous
responses.
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In self-administered surveys, it is useful to provide instructions
on the format of the response that is required so as to minimize
opportunities for the respondents to answer the question
according to very different dimensions.
CONTINGENCY QUESTIONS
A contingency question is a special case of a closed-ended
question because it applies only to a subgroup of respondents.
The relevance of the question for a subgroup is determined by
asking a filter question.
The filter question directs the subgroup to answer a relevant set
of specialized questions and instructs other respondents to skip
to a later section of the questionnaire.
The advantage of contingency questions is that detailed data
may be obtained from a specific subgroup of the population.
Some questions may apply only to females and not to males;
others may apply only to people in school, and not to those who
are employed.
At the base of good contingency questions are clear and specific
instructions to respondents. The formats for filter and
contingency questions can vary. One option is to write
directions next to the response category of the filter question.
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Are you enrolled in secondary school?
1. Yes (answer the following question)
2. No (skip to question 5)
Alternatively, the contingency question can be placed at the end of
the questionnaire set apart from ordinary questions that are to be
answered by everybody:
ANSWER THIS FINAL SET OF QUESTIONS ONLY IF YOU PLAN ON
ENTERING AN ADULT EDUCATION COURSE NEXT YEAR.
OTHERWISE, YOU HAVE NOW COMPLETED THE QUESTIONNAIRE.
INTERVIEWS:
TYPES:
STUCTURED AND UNSTUCTURED:
STRUCTURED INTERVIEWS
A structured interview is when the interviewer has a series of
questions written down on a piece of paper, and the process
involves asking those questions verbatim and then noting the
answers given.
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Sometimes the script for a structured interview is created in
advance by the interviewer, and other times it is given to her by
the human resources department.
It is not uncommon for an interviewer to prefer the structured
interview and spend time creating a customized script for each
interview.
Other interviewers use a standard script that has been approved
by the human resources department.
UNSTRUCTURED INTERVIEW
An unstructured interview is one where there may be a script to
get the process started, but once the interview gets going the
interviewer will start to follow her own points of interest and
stop following any script.
You will find that some managers use unstructured interviews in
a business setting. An unstructured interview helps in
examining an issue that may not have been outlined in a resume
or application but is still relevant to the job.
The unstructured interview is also used in media interviews with
celebrities. The interviewer may find the subject's thoughts on a
particular topic interesting and relevant to the conversation,
and the unstructured format allows the interviewer to pursue
that line of questioning deeper.
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DIFFERENCES
A candidate will prepare for an interview whether it is
structured or unstructured, but it is easier to find out how a
candidate performs under pressure in an unstructured
interview.
With an unstructured interview it is also possible to explore
statements that may come up during the course of the interview
that the interviewer may not have been expecting.
Examples include reasons for leaving previous jobs or details
about past job experiences that may not be mentioned in a
resume.
A structured interview allows the company to find out exactly
what it needs to help quickly determine if a candidate should
move on to the next level of the interview process. A structured
interview also takes the pressure off of the interviewer as he
will know exactly what to ask next.
A structured interview is an effective tool for the phone
interview and the initial interview in the hiring process. It can
help to weed out candidates that do not have the necessary
qualifications.
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The unstructured interview is effective in finding out more
about a candidate's personality, how a candidate reacts in a
pressure situation and in learning other details about a
candidate before making a hiring decision.
OTHER TYPES:
TRADITIONAL FACE-TO-FACE INTERVIEW
a. Most interviews are face-to-face. The most traditional is a one-
on-one conversation.
b. Your focus should be on the person asking questions. Maintain
eye contact, listen and respond once a question has been asked.
c. Your goal is to establish rapport with the interviewer and show
them that your qualifications will benefit their organization.
PANEL/COMMITTEE INTERVIEW
a. In this situation, there is more than one interviewer. Typically,
three to ten members of a panel may conduct this part of the
selection process.
b. This is your chance to put your group management and group
presentation skills on display.
c. As quickly as possible, try to 'read' the various personality types
of each interviewer and adjust to them. Find a way to connect
with each interviewer.
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d. Remember to take your time in responding to questions.
Maintain primary eye contact with the panel member who asked
the question, but also seek eye contact with other members of
the panel as you give your response.
BEHAVIOURAL INTERVIEW
a. The basic premise behind this type of interview is that your past
behaviour is the best predictor of your future actions. These
types of questions may be asked in any interview format
telephone, panel or one-on-one.
b. If the employer asks behaviour-oriented questions, they are no
longer asking hypothetical questions but are now asking
questions that must be answered based on facts.
c. With a behavioural question, the interviewer is looking for
results, not just an activity list. They are listening for names,
dates, places, the outcome and especially what your role was in
achieving that outcome.
d. This type of question generally starts with the words Give me
an example when... or Tell me about a time when
CASE INTERVIEW
a. In some interviews you may be asked to demonstrate your
problem-solving skills. The interviewer will outline a situation or
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provide you with a case study and ask you to formulate a plan
that deals with the problem.
b. You do not have to come up with the ultimate solution. The
interviewers are looking for how you apply your knowledge and
skills to a real-life situation.
c. Speak and reason aloud so interviewers have a full
understanding of your thought process.
d. Before answering a case interview question, be prepared to ask
the employer numerous questions for clarity and informational
purposes. Most employers will provide responses that could
result in additional inquiries.
e. The more you are able to analyze and dissect the case study,
the more you will likely impress your interviewer.
f. This is the only interview for which it is acceptable, even
encouraged, to bring a pad of paper and pencil. Most
interviewers will allow