Slide 1
It is a framework or plan or Blueprint developed to control the
collection of data is called research design.
Research design is an absolute essentiality in research
irrespective of the type of research (e.g., exploratory or
descriptive), as it ensures that the data collected is appropriate,
economical and accurate.
RESEARCH DESIGN
1
A research design is the arrangement of conditions for
collection and analysis of data in a manner that aims to combine
relevance to research purpose with economy in procedure.
A research design is a conceptual structure within which
research is conducted; it constitutes the blue print for the
collection, measurement and analysis of data.Meaning
An activity and time based plan.
A plan always based on the research question.
A guide for selecting sources and types of information.
A framework for specifying the relationship among the studys
variable.
A procedural outline for every research activity.
What is the study about?
Why is the study being made?
Where will the study be carried out?
What type of data is required?
Where can the required data be found?
What time period the study includes?
What will be the sample design?
What techniques of data collection to be used?
How will the data be analyzed?
In what style the report be prepared?Components of research
design
It is a plan that specifies the sources and types of information
relevant to the research problem.
It is a strategy specifying which approach will be used for
gathering and analyzing the data.
It includes the time and cost budget since most studies are done
under these two constraints.
important features of research design
Research design must, contain
A clear statement of the research problem;
Procedures and techniques to be used for gathering
information;
The population to be studied; and
Methods to be used in processing and
Analyzing data. important features of research design
Research Design is needed because it facilitates the smooth
sailing of the various research operations, thereby making research
as efficient as possible yielding maximal information with minimal
expenditure of effort, time and money.
Need for research design
It stands for advance planning of the methods in collecting
relevant data and techniques to be used in their analysis, keeping
in view the objective of the research and the availability of
staff, time and money.
The design helps the researcher to organize his ideas in a form
whereby it will be possible for him to look for flaws and
inadequacies.Need for research design
FEATURES OF GOOD DESIGNA good design is often characterized by
flexible, appropriate, efficient and economical. The design which
minimizes bias and maximizes the reliability of the data collected
and analyzed is considered a good design. The design which gives
the smallest experimental error is supposed to be the best design
in many investigations. A research design which yields maximal
information and provides an opportunity for considering many
different aspects of a problem is considered most appropriate and
efficient design in respect of many research problems.The question
of good design is related to the purpose or objective of the
research problem and also with the nature of the problem to be
studied.One single design cannot serve the purpose of all types of
research problems.
VARIABLES
A concept which can take on different quantitative values is
called variables. As such concepts like weight, height, income are
all examples of variables.
Continuous Variables - Age is an example Non Continuous
Variables - Number of children Dependent & Independent
VariablesEg. For instance height depends upon age, then Height is a
dependant variable and Age is an independent variable.
The Independent Variable (IV) is the causal variable The
Dependent Variable (DV) is the effect variable
Extraneous VariablesIndependent variables that are not related
to the purpose of the study, but may affect the dependant variable
are termed as extraneous variable.
Multiple VariablesYou are interested in finding out which color,
type, and smell of flowers are preferred by butterflies for
pollination. Control
Basic Research Objectives and Research Design
To gain background information, to define terms, to clarify
problems and develop hypotheses, to establish research priorities,
to develop questions to be answered- ExploratoryTo describe and
measure marketing phenomena at a point in time- DescriptiveTo
determine causality, test hypotheses, to make if-then statements,
to answer questions-Causal
Types of Research Design
Exploratory Research Design
Exploratory research is conducted to explore a problem at its
preliminary stage, to get some basic idea about the solution at
preliminary stage of a research study.
It is most commonly unstructured, informal research i.e.
undertaken to gain background information about the general nature
of the research problem.
The major purpose of exploratory research to identify the
problem more specifically.
Exploratory study is used in the initial stages of research.
In the early stage of research, we usually lack from sufficient
understanding of the problem to formulate a specific hypothesis.
Further, there are often several tentative explanations.
Example: Sales are down because our prices are too high, our
dealers or sales representatives are not doing a good job, Our
advertisement is weak and so on. In this scenario, very little
information is available to point out, what is the actual cause of
the problem.
Under what circumstances is exploratory study ideal?
To gain an insight into the problemTo generate new product
ideasTo list all possibilities. Among the several possibilities, we
need to prioritize the possibilities which seem likely.To develop
hypothesis occasionally.To establish priorities so that further
research can be conducted.To pre-test a draft questionnaire.
Example, a shirt manufacturer sponsored a survey to find the
percentage of executives purchasing different sizes a shirt. The
researcher was asked to record the sizes 36, 38, 40, 42, 44 as
indicated by the executives. The exploratory survey indicated that
quite a good percentage of executives indicated the size as 39 and
41 (which were either imported or tailor made). This information
led to change the questionnaire to include these options.
Exploratory Research Methods
Literature SearchThis 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 analysed 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.
The companys market share has declined but industrys figures are
normal.The industry is declining and hence the companys market
share is also declining.The industrys share is going up but the
companys share is declining.
Experience survey An exploratory research technique in which
individuals who are knowledgeable about particular research problem
are surveyed.When we interview persons in an experience survey, we
should seek their ideas about important issues or aspects of the
subject and discover what is important across the subjects range of
knowledge.
What is being done?What has been tried in the past without
success?How have things changed?What problems areas and barriers
can be seen?Who is involved in decisions and what roles does person
play?
Focus groupMost widely used technique.
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 8-12 persons.
While selecting these persons, care 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.
Focus groups should be taped (audio) or videoed. Videoing can be
more difficult and intrusive but is often worthwhile.
Permission of the participants should always be sought for
taping/ videoing.
The following should be the characteristics of a moderator/
facilitator:
ListeningMemoryEncouragementLearningSensitivityIntelligenceKindly
firm
Case studiesAnalyzing 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 studies are well studied to carry out exploratory
research. However the result of investigation of case histories are
always considered suggestive, rather than conclusive.
CONCLUSIVE RESEARCHThis is a research having clearly defined
objectives.
In this type of research, specific courses of action are taken
to solve the problem.
Conclusive research are of two types.
Descriptive researchIt concerned with describing the
characteristics of a particular individual , group , frequency of
occurrence.
Researcher must able to define clearly, what he wants to measure
and must find adequate methods for measuring it along with the
clear cut definition of population
Descriptive research is undertaken to provide answers to
questions of who, what, where, when, why and how.
Descriptive research studies are those studies which are
concerned with describing the characteristics of a particular
individual, or a group.
When to use descriptive study?
To determine the characteristics of market such asSize of the
marketBuying power of the consumerProducing usage patternTo find
out the market share for the productTo track the performance of a
brandTo determine the association of the two variable such as Ad
and salesTo make a prediction. We might be interested in sales
forecasting for the next three years, so that we can plan for
training of new sales representatives.To estimate the proportion of
people in a specific population, who behave in a particular way?
Example: What percentage of population in a particular geographical
location would be shopping in a particular shop?
Adjective typifying the researchIllustrative questionWhoWho has
been most consistent batsman among Sachin, Dravid and Ganguly in
the test matches?WhichWhich is the cricket ground where maximum
number of centuries have been scored?Which are the companies that
have declared more than 50% dividend for the year
2010-2011?WhatWhat is the average salary offered to MBA students
with marketing specialisation? WhereWhere the responses to a
particular advertisement were most favourable, among all the major
cities where the test marketing was carried out?WhenWhen did the
manufacturing process go out of controlHow (Much, Many)How much
productivity increased in an organisation after a training to the
employees?How many Mutual funds have paid more than 10% dividend
for their Tax Saver Scheme.
Longitudinal study
These are the studies in which an event or occurrence is
measured again and again over a period of time.
This is also known as Time Series Study. Through longitudinal
study, the researcher comes to know how the market changes over
time.Longitudinal studies are quite poplar in social and
behavioural sciences, socio economic research, banking and finance
etc.
Examples areExperiment pattern over a period of time of an
individual or group of individuals. R& D Expenditure by a
sector of companies like pharmaceuticals etc.
Quality of Life parameters of a state or a country.Longitudinal
research relies on panel data and panel methods.
It involves fixing a panel consisting of fixed sample of
subjects that are measured repeatedly.
The panel members are those who have agreed to provide
information at a specific interval over an extended period.
For example, data obtained from panels formed to provide
information on market shares are based on an extended period of
time, but also allow the researcher to examine changes in market
share over time. New members may be included in the panel as an
when there is a dropout of the existing members or to maintain
representativeness.
Two types of panel are
Advantages of Longitudinal studies
Discover trends and patterns of change
Locate the times when the trend or pattern changed - it might
lead to investigating the factors that cased the change.
Cross sectional studyThese are the studies that are conducted
over a group of companies or organizations over the same point of
time. Such research makes observations at one and the same point of
time for all the entities under study.
Example: Placement offers to MBA students of 2011 batch at all
IIMs.P/E ratio of all automobiles companies as on 31st March
2012Conducting opinion poll on a particular day
The major advantage of cross-sectional research is that data can
be collected on many entities of different kinds in a short span of
time. Since the data is collected at one point of time, it can be
easily collected at LOWER COST.
Cross sectional study is that it is cheaper and faster to
conduct such a study. The main disadvantage of such study is that
it reveals little as how to how the changes occur. Cross sectional
design may be either single or multiple cross sectional design
depending on the number of samples drawn from a population.
Cohort analysis consists of a series of surveys conducted at
appropriate time intervals, where the cohort serves as the basic
unit of analysis.
A cohort is a group of respondents who experience the same event
within the same time interval.
EXPERIMENTAL RESEARCH OR CASUAL RESEARCH
The casual research is concerned with finding the root cause of
a symptom.
For example, if the sale of a product is declining, or if
customers prefer a product over other similar product(s), one may
like to know the cause(s) for the same.
Thus, this type of study encompasses situations where we study
the impact or influence of one factor (cause) on some other factor
(effect). The influencing factors could be one or more than
one.
Some of the examples of casual research are
The factors influencing buying behaviour of customers.
The factors influencing the motivating of an
employee.Advertising expenses is the cause (called independent
variable) and
Sales (called dependent variable) is the effect.Casual variables
is also called explanatory variable as it explains the effect or
impact on the dependent variable.
Experimental ResearchAn experiment is defined as manipulating
(changing values/situations) one or more independent variables to
see how the dependent variable(s) is/are affected, while also
controlling the affects of additional extraneous variables.
Independent variables: those over which the researcher has
control and wishes to manipulate i.e. package size, ad copy,
price.
Dependent variables: those over which the researcher has little
to no direct control, but has a strong interest in testing i.e.
sales, profit, market share.
Extraneous variables: those that may effect a dependent variable
but are not independent variables.
TYPES OF EXPERIMENTS
Basic principles of experimental designs
The principle of Replication
The principle of Randomization
The Principle of Local control
Types of Experiment Research Design
VALIDITY OF RESEARCH DESIGN
Validity refers to the strength and the accuracy of a research
design. Two types of validity in a research design viz.
Internal Validity
Internal validity describes the ability of the research design
to unambiguously (clearly) test the research hypothesis. Internal
validity refers to the extent to which one can accurately state
that the independent variable is responsible for the observed
effect in the dependent variable and no other variable is
responsible for the effect.
If the effect on dependent variable is only due to variation in
the independent variable, then we may conclude that the internal
validity is achieved.
Threats of internal validity
History
History refers to the events that are beyond the control of the
experiment.
These events may change the attitude of the respondents
irrespective of whether the independent variable is changed or
not.
Thus it is impossible to determine whether any change on the
dependent variable is due to the independent variable or the
historical event.
Maturation
History refers to the events that are beyond the control of the
experiment.
These events may change the attitude of the respondents
irrespective of whether the independent variable is changed or
not.
Thus it is impossible to determine whether any change on the
dependent variable is due to the independent variable or the
historical event.
Testing
Repeatedly measuring the participants may lead to bias.
Participants may remember the correct answers or may be conditioned
to know that they are being tested.
Selection of respondentsThe inappropriate selection of
respondents may lead to bias in experiemental design. If the
selected respondents are not uniform, inadvertent randomization may
take place leading to bias.Statistical regressionThe statistical
regression refers to the bias that may crop in due to some
respondents giving extreme responses. This bias is known as error
sum of squares in statistical regression analysis.
Experimental MortalityThis can occur when the respondents drop
out during the experiment especially in the experiment involving
pre test and post test. The same respondents who take up the
pre-test may not be available for the post-test. This results in
excluding the entire pre test data from the analysis dropped out
respondents.
Instrument change (instrumentality)
The instrument used during the testing process can change the
experiment. This also refers to observers being more concentrated
or primed, or having unconsciously changed the criteria they use to
make judgments.
EXTERNAL VALIDITY
External validity is related to generalisability of the
findings/results. It refers to the degree of generalisability of
the conclusions to other situations.
In other words, external validity is the degree to which the
conclusions in the study for a given population could be made
applicable to other populations or other situations.
Meaning A business research study, involves study of
characteristics of an individual/item/unit entity etc. These
characteristics are represented by variables.
As the name suggests a variable changes values for different
individual/item at the same time Example: Income of individuals for
the year 2009-10, prices of stocks on a day) or for the same
individual/item at different time (income for an individual, sales
of a company).VARIABLES IN RESEARCH
Independent variable
Dependent variable
Moderating variable
Intervening variable
Extraneous variable
Continuous variable
Non-continuous/Discrete variableTYPES OF VARIABLES
The process of assigning numbers to objects or observations, the
level of measurement being a function of the rules under which the
numbers are assigned.
It is easy to assign numbers in respect of properties of some
objects, but it is relatively difficult in respect of others. For
instance, measuring such things as social conformity, intelligence,
or marital adjustment is much less obvious and requires much closer
attention than measuring physical weight, biological age or a
persons financial assets. MEASUREMENT AND SCALING TECHNIQUES
In other words, properties like weight, height, etc., can be
measured directly with some standard unit of measurement, but it is
not that easy to measure properties like motivation to succeed,
ability to stand stress and the like.MEASUREMENT AND SCALING
TECHNIQUES
Measurement Scales
A qualitative scale without order is called nominal scale.
Nominal scale is the least powerful level of measurement.
It indicates no order or distance relationship and has no
arithmetic origin.
A nominal scale simply describes differences between things by
assigning them to categories.
Nominal data are, thus, counted data.Nominal scale
In research activities a YES/NO scale is nominal.
It has no order and there is no distance between YES and NO.
The statistics which can be used with nominal scales are in the
non-parametric group.
ModeCross tabulation - with chi-square
Nominal scale
Example: The terms we use for colours. The colour of bike is a
nominal measure. Which colour will you prefer for a bike? could be
blue, black, red, etc. One may number these colours as 1, 2, 3 etc
in any sequence i.e. this scale neither has any specific order nor
it has any value.
Ordinal ScaleWith ordinal scales, it is the order of the values
is whats important and significant, but the differences between
each one is not really known.
Like in a competition. A qualitative scale with order is called
an ordinal scale. This scale posses the properties of distinctive
classification and order.
Ordinal Scale Rank as a measure is always considered as
ordinal.
The difference between any two ranks is not necessarily equal.
The difference between first and second rank does not connote the
same differential.
For example in a class of students, the highest mark is 95, next
highest is 85 and the next is 84, converting marks into ranks will
lead to 1, 2 and 3.
Incidentally, it may be noted that the difference in the
performance of the 1st ranker and 2nd ranker is not the same as the
2nd ranker and 3rd ranker.
Statistics tool applied in Ordinal scale Ordinal data would use
non-parametric statistics. These would include:
Median and mode
Rank order correlation
Non-parametric analysis of variance
Modelling techniques can also be used with ordinal data.
Interval ScaleInterval scales are numeric scales in which we
know not only the order, but also the exact differences between the
values.
The classic example of an interval scale isCelsiustemperature
because the difference between each value is the same. For example,
the difference between 60 and 50 degrees is a measurable 10
degrees, as is the difference between 80 and 70 degrees. Time is
another good example of an interval scale in which theincrementsare
known, consistent, and measurable.
Central tendencycan be measured by mode, median, or mean;
standard deviation can also be calculated.This is a quantitative
scale of measure without a fixed or true zero. For example, there
is no such thing as no temperature.
Without a true zero, it is impossible to compute ratios. With
interval data, we can add and subtract, but cannot multiply or
divide. Confused? Ok, consider this: 10 degrees + 10 degrees = 20
degrees. No problem there. 20 degrees is not twice as hot as 10
degrees, however, because there is no such thing as no temperature
when it comes to the Celsius scale.
When you are asked to rate your satisfaction with a piece of
software on a 5 point scale, from Dissatisfied to Satisfied, you
are using an interval scale.
Statistical tools Interval scale data would use parametric
statistical techniques:
Mean and standard deviationCorrelation rRegression
Analysis of varianceFactor analysisAdvanced multivariate and
modelling techniques.
Ratio scalesRatio scales have an absolute or true zero of
measurement. We can conceive of an absolute zero of length and
absolute zero of time.
Ratio scales represents the actual amount of variables. Measures
of physical dimensions such as height, weight, distance etc are
examples.
All statistical techniques are usable with ratio scales.
Multiplication and division can be used with this scale but not
with other scales.
Geometric and Harmonic means can be used as measure of central
tendency and coefficients of variation also be calculated.
Scaling
Scaling has been defined as a procedure for the assignment of
numbers (or other symbols) to a property of objects in order to
impart some of the characteristics of numbers to the properties in
question.
The number assigning procedures or the scaling procedures may be
broadly classified on one or more of the following bases: (a)
Subject orientation; (b) Response form; (c) Degree of subjectivity;
(d) Scale properties; (e) Number of dimensions and (f) Scale
construction techniques.
Selection or construction of a measurement scale requires
decision in the following six key areas:
Study objective
Response form
Degree of preference
Data properties
Number of Dimensions
Scale construction
Construction of measurement scales
Arbitrary scales are developed on ad hoc (unplanned) basis. It
is largely based on researchers own subjective selection of items.
Several items, which are appropriate and unambiguous to the theme
of study, may be selected.
Each item is scored from 1 to 5 depending on the responses
obtained. The results are then totaled.
Arbitrary scales are easy to develop, inexpensive and highly
specific to the theme of the study.
The major limitation is that the design approach is
subjective.Arbitrary scales
In consensus scale the items are selected by a panel of judges
after evaluation on the basis of some criteria like
Relevance to the topic area
The risk of ambiguity and
The level of attitude represented by the items.Consensus
Scaling
This scale is rarely used for measuring Organizational concepts
- because of time.
One of Consensus scale is The Thurstone Equal Appearing Interval
Scale by using a pile of cardConsensus Scaling
This approach is widely known asThurstonequal appearing Interval
Scale. The procedure followed in construction of the scale is
described belowStep: 1 A large number of items/statements
expressing different degree of favorableness towards an object
relating to the subject of the study, usually more than twenty are
collected by the researcher.
Step: 2 A panel of judges evaluates the statements. The
statements are written in the card.
Step: 3 The judges sort each card into one of the 11 piles
representing the degree of favorableness the statement
expresses.
Step: 4 The sorting yields a composite position for each of the
items. In case of disagreement between the judges the item is
discarded.Step: 5 For the items that are retained median scale
value between one and eleven is assigned.Step: 6 A final selection
of statements is made on the basis of the median score. Of the 11
piles 3 are identified by the judges as favourable , unfavourable
and neutral. The eight intermediate piles are unlabelled.
Theitemized rating scaleis a 5 point or 7 point scale with
anchors provided for each item and the respondent states the
appropriate number on the side of each item or circles the relevant
number against each item. The responses to the items are then
summated.This uses an interval scale. Example is shown below;
indicate your response number on the line for each item.1234 5Very
Unlikely UnlikelyNeither UnlikelyLikely Very Likely nor likelyItem
Analysis scaling
I like to take more responsibility -----
If additional responsibility is not provided I will be
dissatisfied -----I am interested in a job which provides me more
salary -----
Step :1 Discriminates between those persons whose score is high
and those whose total score is low. Step :2 It involves calculating
the mean score for each scale item among the low scorers and high
scorers. The item means between the high-score group and the
low-score group are then tested for significance by
calculatingtvalues.Step :3 Finally the items that have the
greatesttvalues are selected for inclusion in the final scales.Item
Analysis scaling
Summated scales consist of a number of statements which express
either favourable or unfavourable attitude towards an object to
which the respondents is required to react. The respondents
indicate the agreement or disagreement with each of the
statement.
Each response is given a numerical score and the total is
obtained to measure the respondents attitude. Summated scales or
Likert scalesare developed by the item analysis approach.
Procedure for developing a Likert type scale
A large number of statements relevant to the object being
studied is collected.
The statement expresses definite favourableness or
unfavourableness towards the subject.
A trial test can be conducted with a small group of respondents
who form part of the final study. The agreement or disagreement
towards each statement is obtained on a five-point scale.
The response is scored in such a way that the response
indicating the most favorable attitude is given the highest score
of 5 and the most unfavorable attitude is given the lowest score
1.
5. The total score of each respondent is obtained by adding the
score for each individual statement.6. The next step is to array
the total scores and find out those statements, which have a high
discriminatory power. For this purpose the researcher may select
some part of the highest and the lowest total scores, for eg, top
25 percent and bottom 25 percent.
7. These two extreme groups are interpreted to represent the
most favourable and the least favourable attitudes and are used as
criterion groups by which to evaluate individual statements.
Thus the statements, which consistently correlate with low
favourability and with high favorability, are identified.
Advantages of Likert scale
It is relatively easy to construct, considered to be more
reliable and less time consuming.
Disadvantages of Likert scale
One of the major limitations is that the scale simply examine
whether respondents are more or less favourable towards the subject
under study, but it cannot reveal how much more or less they
are.
There is no basis for belief that the five positions indicated
on the scale are equally spaced.
Cumulative scales consist of series of statements to which a
respondent expresses his agreement or disagreement. An individual
whose attitude is at a certain point in a cumulative scale will
answer favourably all the items on one side of this point and
answer unfavourably all the items on the other side of this
point.
The individuals score is arrived at by counting the number of
points concerning the number of statements answered favourably.
Cumulative scales
If the total score is known it is easy to estimate the
respondent does answer to individual statements constitute the
cumulative scales.
A major scale of this type is the Guttmans scalogram.Scalogram
analysisrefers to the procedure for determining whether a set of
items forms a one-dimensional scale.
A scale is one dimensional if the responses fall into a pattern
in which endorsement of the item reflecting the extreme position
results also in endorsing all items, which are less extreme.
Factor scales includes a variety of techniques that been
developed to address two issues viz, the problem of dealing with
the universe of content that is multi dimensional and the problem
of uncovering the underlying dimensions that has not been
identified by the exploratory research.
Factor scales are developed through factor analysis or on the
basis of inter correlations of items, which indicate the common
factor responsible for the relationships between items.
Factor scales
Semantic Differential Scale
Multidimensional scaling (MDS)
Different types of factor analysis
Semantic Differential Scale
Developed by Charles E.Osgood, G.J. Suchi and P.H. Tannenbaum
(1957),
It is an attempt to measure the psychological meanings of an
object to an individual.
This scale is based on the presumption that an object can have
different dimensions of connotative meanings which can be located
in multidimensional space.
This scaling consists of a set of bipolar rating scales, usually
of 7 points, by which one or more respondents rate one or more
concepts on each scale item.
3210-3-2-1(E) SuccessfulUn Successful(P) SevereLenient(P) Heavy
(A) Hot(E) Progressive(P) Strong(A) ActiveLightCold
RegressiveWeakPassiveFor instances, the S.D scale items for
analyzing candidates for leadership position May be shown as
under:
Candidates for leadership position may be compared and score
them from -3 to +3 on the basis of the above stated scales. The
letters E,P, A stands for
E EvaluationP PotencyA Activity
Written along the left side are not written in actual scale. The
numeric values shown are also not written in actual scale.
Osgood and others conclude that Semantic space is
multidimensional rather than unidimensional.
The semantic differential has several advantages. It produces
interval data. It is an efficient and easy way to elicit responses
from a large sample.The attitudes can be measured both in terms of
direction and intensity. The total set of responses provides a
comprehensive picture of the meaning of an object. It is a
standardized technique which can be easily repeated and at the same
time escapes many problems of response distortion.
Multidimensional scaling
Multidimensional scaling is relatively more complicated scaling
device which can be used to scale objects, individuals or both with
a minimum of information.It enables to provide visual impression of
the relationship between variables.
The MDS enables the researcher to study the perceptual structure
of a set of stimuli and the cognitive process underlying the
development of this structure.
It enables perceptual mapping in a multidimensional space.
Multidimensional scaling
For example if respondents are asked to identify similar
products among a group of products and if product X and Y are
similar,MDS technique will position X and Y in such a way that the
distance between them in multidimensional space is shorter than
that between any two other objects.
However MDS is not widely used because of the computational
complications involved.
Validity and Reliability of an instrument or TESTS OF SOUND
MEASUREMENT
Test of Validity
Content validity; Criterion-related validity and Construct
validity.
Test of Reliability
3. Test of Practicality