RESEARCH IN INFORMATION SYSTEMS MANAGEMENT

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RESEARCH INRESEARCH IN
INFORMATIONINFORMATION
SYSTEMSSYSTEMS
MANAGEMENTMANAGEMENT
(IMS 603)(IMS 603)

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Why Do Research?Why Do Research?
Research provides you with theResearch provides you with the
knowledge and skills needed for the fast-knowledge and skills needed for the fast-
paced decision-making environmentpaced decision-making environment

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Types of Research StudiesTypes of Research Studies
ReportingReporting
DescriptiveDescriptive
ExplanatoryExplanatory
PredictivePredictive

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Styles of ResearchStyles of Research
Applied ResearchApplied Research
Pure Research/Basic ResearchPure Research/Basic Research
Business ResearchBusiness Research

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What is Good Research?What is Good Research?
Purpose clearly definedPurpose clearly defined
Research process detailedResearch process detailed
Research design thoroughly plannedResearch design thoroughly planned
High ethical standards appliedHigh ethical standards applied
Limitations frankly revealedLimitations frankly revealed

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What is Good Research (cont.)What is Good Research (cont.)
Adequate analysis for decision-Adequate analysis for decision-
maker’s needsmaker’s needs
Findings presented unambiguouslyFindings presented unambiguously
Research design thoroughly plannedResearch design thoroughly planned
Conclusions justifiedConclusions justified
Limitations frankly revealedLimitations frankly revealed

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The ResearchThe Research
ProcessProcessOBSERVATION
Broad Area of
Research
Interest
PROBLEM
DEFINITION
Research
problem
delineated
PRELIMINARY
DATA
GATHERING
Interviews &
Literature
review
THEORETICAL
FRAMEWORK
Variables
clearly
identified
GENERATION
OF
HYPOTHESES
DATA
COLLECTION,
ANALYSIS &
INTERPRETATION
DEDUCTION
Hypotheses
substantiated?
Research
Questions
answered?

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The ResearchThe Research
StagesStages
Framing your Research
Designing your Research
Reporting your Research

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Framing yourFraming your
ResearchResearch
What is your Research Problem?
Why is it Important?
How is your Research related to the present
body of Knowledge?
What are your Research Questions?
What are various Concepts involved in your
Research and how are they interrelated ?
What are their Hypothesized Relationships?

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Designing yourDesigning your
ResearchResearch
What Research Design to use?
What Data to Collect?
Where to Collect your Data From?
How to Analyze your Data?
- Survey vs Experiments
- Measurement
- Sampling Design
- Data Collection
Techniques
- Data Analysis
How to Collect your required Data?

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Final Steps in ResearchFinal Steps in Research
Data analysisData analysis
Reporting the resultsReporting the results
- Executive summary- Executive summary

Overview of the researchOverview of the research

Findings, Implementation strategies forFindings, Implementation strategies for
the recommendationsthe recommendations

Technical appendixTechnical appendix

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Problem StatementProblem Statement
Existing problem that requires solution
Specific areas in the organisation requiring
improvement
Eg. Complaint of harrassment by senior officers
E.g When policy about “harassment” exist but genuine
complaint still occur
Theoretical or conceptual issue that needs tightening up
Eg: What is meant by “harrassment”
Research questions that basic researcher needs to
answer empirically
E.g: Impact of “harrassment” on performance

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Literature ReviewLiterature Review
Purpose: Gather related information of research areas
Why?
Avoid “reinventing the wheel”
We do not missed out important variables
Problem statement can be stated precisely and
accurately
“Testability” and “replicability” of findings
Clearer idea of what are the important variables

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Research Question HierarchyResearch Question Hierarchy
Management Dilemma
Level 5
Level 4
Level
3
Level
2
Level
1
Measurement Questions
Investigative Questions
Research Questions
Management Questions

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Examples of ProblemExamples of Problem
StatementsStatements
To what extent the organizational structure and type of
information system implemented explain the
effectiveness of managerial decision-making?
To what extent the SSB has enhances the motivation
level of civil servants?
Does leadership style influence the number of
turnover?

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Theoretical FrameworkTheoretical Framework
A conceptual model that depict how YOU relate all
the important variables identified in your study.
Helps you generate and test the relationships to
enhances your understanding of the dynamics of the
problem.
Consists of variables and relationships between the
variables.

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Example of a TheoreticalExample of a Theoretical
FrameworkFramework
Air traffic
violations
Communication
between cockpit crew
Communication
between cockpit and
air traffic tower
Decentralization
Crew training
Independent
variables
Dependent Variable

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Example of a TheoreticalExample of a Theoretical
FrameworkFramework
Air traffic
violations
Communication
between cockpit crew
Communication
between cockpit and
air traffic tower
Decentralization
Crew training
Independent
variables
Dependent
Variable
Nervousness
Intervening
Variable

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Example of a TheoreticalExample of a Theoretical
FrameworkFramework
Air traffic
violations
Communication
between cockpit crew
Communication
between cockpit and
air traffic tower
Decentralization
Independent
variables
Dependent
Variable
Moderator
Variable
training

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Hypothesis GenerationHypothesis Generation
An hypothesis is a relationship that is assumed based
upon logic, between two or more variables in the form
that is testable.
Format 1: Differences
Testing and validating an assumed hypothesis can
leads to problem solution.
Format 2: If-then

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Examples ofExamples of
HypothesesHypotheses
If communication among crew is good then the
number of air traffic violation will be reduced
Good training among crew members will reduced
nervousness and subsequently reduces the number of
air traffic violations.
If the communication among crew members is good
then the number of air traffic violations will be
reduced provided they had sufficient training.

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Research DesignResearch Design
PROBLEMSTATEMENT
Purpose of
Study
•Exploration
•Description
•Testing
Types of
Investigation
•Relationship
•Correlation
•Group
differences
Unit of
Analysis
•Individual
•Dyads
•Groups
•Organizations
Sampling
Design
•What/Who?
•How many?
Study
Setting
•Contrived
•Noncontrived
Researcher
Interference
•Minimal
•Manipulation
/ control/
simulate
Time Horizon
•Cross-sectional
•Longitudinal
Measurement
•Items
•Scaling
•Categorizing
•Coding
Data
Collection
•Observation
•Interviews
•Physical
•Unobstrusive
DATAANALYSIS
•Feelfordata
•Goodnessofdata
•Testing

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What data to collect?What data to collect?
Issue of measurement:Issue of measurement:
Measurement must beMeasurement must be validvalid andand
reliablereliable
Source:Source:

LiteratureLiterature

Self-developSelf-develop

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MeasurementMeasurement
““Development of science is nothingDevelopment of science is nothing
but the development of measurement”but the development of measurement”
““Whenever you can, count”Whenever you can, count”
““Everything that countsEverything that counts
should be counted”should be counted”

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MeasurementsMeasurements
Empirical research often implies measurementsEmpirical research often implies measurements
Quality of information depends on theQuality of information depends on the
measurement processmeasurement process
Measurement Defined:Measurement Defined:

The mapping of some propertiesThe mapping of some properties

Rules for assigning numbers to empirical propertiesRules for assigning numbers to empirical properties

Rules: specify the procedure according to whichRules: specify the procedure according to which
numbers are to be assigned to objectsnumbers are to be assigned to objects

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Working DefinitionsWorking Definitions
 MeasurementMeasurement is a process through which theis a process through which the
kind or intensity of something is determined: i.e.kind or intensity of something is determined: i.e.
measurement ismeasurement is

the process of linking abstract concepts to empiricalthe process of linking abstract concepts to empirical
indicants.indicants.
 DimensionalityDimensionality refers to the number of differentrefers to the number of different
qualities inherent in a theoretical concept.qualities inherent in a theoretical concept.
 AA conceptconcept is a general idea referring to ais a general idea referring to a
characteristic of an individual, group, or a nation.characteristic of an individual, group, or a nation.

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Working DefinitionsWorking Definitions
Example:Example:
•
The Theoretical Concept:The Theoretical Concept: Social StatusSocial Status
•
Dimensions:Dimensions: Occupational Prestige,Occupational Prestige,
Ethnicity, Popularity, EducationalEthnicity, Popularity, Educational
Prestige, Financial Resources, and so on.Prestige, Financial Resources, and so on.

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How are Variables Measured?How are Variables Measured?
Objective – precise measurementObjective – precise measurement
Subjective – nebulous & abstract; e.g.Subjective – nebulous & abstract; e.g.
attitude, beliefs, involvement,attitude, beliefs, involvement,
satisfactionsatisfaction
Concept ofConcept of “Thirst”“Thirst”
Process of reducing abstract concept toProcess of reducing abstract concept to
measurable items is calledmeasurable items is called
OperationalizationOperationalization

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OperationalizationOperationalization
Concept
Operational
Definition
Dimensions
A generalized idea about a class of
objects, attributes, occurrences, or
processes e.g. sex, loyalty
Gives meaning to a concept by
specifying the activities or operations
necessary to measure it
Elements
Broad characteristics to ensure
coverage or scope of the concept
Specific items about the identified
measurement, which are easily
measured

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Operationalizing: LearningOperationalizing: Learning
Learning
Understanding Retention Application
Answer
questions
correctly
Give
appropriate
examples
Recall
material
after some
lapse
Solve
problems
applying
concepts
understood
and recalled
Integrate
with other
relevant
material
e e e e e
d d d

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Operationalizing: MotivationOperationalizing: Motivation
Achievement
Motivation
Driven by
work
Unable
to relax
Impatience with
ineffectiveness
Constantly
working
Reluctance
to take
time off
e
d
Seeks moderate
challenges
Seeks
feedback
Persist
despite
setbacks
Work at
home
No hobby
Swears at
small
mistakes
Does not like
to work with
incompetent
people
Opt for
challenging
not routine
Opt for
moderate
rather than
overwhelming
challenge
Ask for
feedback
about job
done
Wants
immediate
feedback

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Operational definition isOperational definition is
NOTNOT
CorrelateCorrelate
AntecedentsAntecedents
ConsequencesConsequences
ReasonsReasons
…… of the conceptof the concept


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ScalesScales
A tool or mechanism by whichA tool or mechanism by which
individuals are distinguished on howindividuals are distinguished on how
they differ from one anotherthey differ from one another
E.g. how do we distinguish individualE.g. how do we distinguish individual
A from B in terms of learning?A from B in terms of learning?
Also refers to level of measurementAlso refers to level of measurement

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Levels Of MeasurementsLevels Of Measurements
Empirical
Scale
Basic
Operations
Measures of
Typical use
Averages
Nominal Determination of
equality
Classification
Male-Female
Occupations
Mode
Ordinal Determination of
greater or less
Ranking
Preference
Attitude
Median
Interval Determination of
equality of intervals
Index numbers
Temperature
Mean
Ratio Determination of
equality of ratios
Sales
Unit produced
No. of customers
Mean
Geometric

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Nominal ScaleNominal Scale
Classificatory or Categorical
e.g. Sex – Male/Female
Colour
Mutually exclusive & collectively
exhaustive

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Ordinal ScaleOrdinal Scale
Categorize and rank
e.g. Preference in job attributes
Please rank from 1 most important to 5 least
important the following attributes:
Interacting with others
Using multiple skills
Completing a task from beginning to end
Serving others
Work independently

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Interval ScaleInterval Scale
Allows for measurement of distance between
two points on the scale
e.g. Preference in job attributes
Using a scale of 1 (strongly disagree), 2 (disagree), 3 (neither agree
nor disagree), 4 (agree) and 5 (strongly agree), please indicate the
extent of your agreement by circling the appropriate number.
The following are very important to me
Interacting with others 1 2 3 4 5
Using multiple skills 1 2 3 4 5
Complete a task from beginning to end 1 2 3 4 5
Serving others 1 2 3 4 5
Working independently 1 2 3 4 5

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Ratio ScaleRatio Scale
Has absolute zero; thus allowing for not
only differences but also proportions in the
differences
e.g. Number of years in the organization

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Properties of the 4 ScalesProperties of the 4 Scales
Characteristics
Difference Order Distance Unique
Origin
Measure of
Center
Measure of
Dispersion
Scale
Nominal
Ordinal
Interval
Ratio
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Mode
Median
Mean
Arithmetic
&Geometric
mean
Semi-
interquartile
range
Standard
deviation
Standard
deviation,
Coefficient
of variation

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Scaling MethodsScaling Methods
Rating Scales
•Dichotomous Scale
•Category Scale
•Likert scale
•Numerical Scale
•Semantic Differential Scale
•Itemized rating scale
•Graphic rating scale
Ranking Scales
•Paired Comparison
•Forced Choice
•Comparative Scale

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Examples: Rating ScaleExamples: Rating Scale
Likert
Do you own a car Yes NoDichotomous
Where do you stay Kedah Penang
Perlis
Category
My work is very interestingMy work is very interesting
Strongly agreeStrongly agree
AgreeAgree
Neither agree nor disagreeNeither agree nor disagree
DisagreeDisagree
Strongly disagreeStrongly disagree

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Examples: Rating ScaleExamples: Rating Scale
How would you rate your work partners
Responsive __ __ __ __ __ __ __ Unresponsive
Semantic
Differential
Numerical
Rating Scale
How please are you with your insurance agent
Extremely Extremely
Pleased __ __ __ __ __ __ __ displeased
Itemized
Rating Scale
Very netiher unlikely Very
Likely likely nor likely unlikely unlikely
1 2 3 4 5
I will be changing my job within the next 3 months __
I will take on new assignment in the near future __

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Examples: Rating ScaleExamples: Rating Scale
Graphic
Rating Scale
On a scale of 1
to 10 how
would you rate
your supervisor
1 Very bad
5 all right
10 Excellent

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Examples: Ranking ScaleExamples: Ranking Scale
When comparing a small number of objects,
respondents are asked to choose between
two objects at a time
Paired
Comparison
Forced Choice
Rank your preferences among the following magazines,
which you would like to subscribe to, 1 being the most
preferred choice and 4 being the least preferred:
Asiaweek __
Economist __
Fortune __
Newsweek __

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Examples: Ranking ScaleExamples: Ranking Scale
Comparative
Scale
In a volatile financial environment, compared to
stocks, how wise or useful is it to invest in bonds?
Please circle the appropriate response.
More usefulMore useful About the sameAbout the same Less usefulLess useful
11 22 33 44 55

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Goodness of MeasuresGoodness of Measures
1. Item Analysis
Test whether items in the instruments
should belong there. Steps:
1. Calculate Total Score
2. Divide respondents into high and
low score
3. Compute t-test for each item
4. Use only items that are significant
2. Reliability
Analysis
Is the measure without bias (error free)
and therefore consistent across time
and across items in the instrument?
i.e. is it stable and consistent?
3. Validity
Analysis
Is the instrument measuring the concept
it sets out to measure and not
something else?

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Goodness of MeasuresGoodness of Measures
GOODNESS
OF DATA
Reliability
(Accuracy)
Validity
(Actuality)
Stability
Consistency
Test-retest
Parallel form
Interitem
consistency
Split-half
Logical
(content)
Criterion
related
Congruent
(construct)
Face
Predictive
Concurrent
Convergent
Discriminant

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Reliability and ValidityReliability and Validity
Valid but Unreliable
Valid & Reliable Reliable but NOT
Valid

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ReliabilityReliability
Observed scores may reflect true scores,Observed scores may reflect true scores,
but it may reflect other factors as well:but it may reflect other factors as well:
stable characteristics: two people having thestable characteristics: two people having the
same opinion may circle different responsessame opinion may circle different responses
transients personal factors such as moodtransients personal factors such as mood
situational factors, time pressure, timesituational factors, time pressure, time
variations in administration and mechanicalvariations in administration and mechanical
factorsfactors
Reliability: Stability and consistencyReliability: Stability and consistency

StabilityStability – over time, conditions, state of– over time, conditions, state of
respondentsrespondents

ConsistencyConsistency – Homogeneity of times; items can– Homogeneity of times; items can
measure the construct independentlymeasure the construct independently

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Reliability of MeasuresReliability of Measures
RELIABILITY
Stability Consistency
Test-retest Parallel form
Repeated
measures on
the same
respondent;
high correlation
– high reliability
Two comparable
sets of measures
for the same
construct; same
items, same
response format
but different
wording; Analysis -
correlation
Interitem Split-half
Consistency of
respondents’
answer to all the
items; high
correlation among
responses to the
items – Cronbach
α
Correlation
between two-
halves of a
measure;
correlation
between the
two halves

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ValidityValidity
Multiple indicators: - often used to capture aMultiple indicators: - often used to capture a
given construct e.g. attitude; togiven construct e.g. attitude; to

cover the domain of the constructcover the domain of the construct

robust - reduce random errorrobust - reduce random error

Cronbach alpha - measures intercorrelationCronbach alpha - measures intercorrelation
between indicators - they should be positivelybetween indicators - they should be positively
correlated but not perfectly correlatedcorrelated but not perfectly correlated
Construct ValidityConstruct Validity

Face validityFace validity

Convergent validity (Correlation to assess it)Convergent validity (Correlation to assess it)

Divergent validityDivergent validity

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ValidityValidity
VALIDITY
Logical
(content)
Criterion
related
Congruent
(construct)
Face
Ensures
adequate and
representative
set of items
that tap the
concept
Panel of judges
– face validity
Predictive Concurrent
Does measure
differentiate to
predict a future
criterion
variable
Analysis –
Correlation
Does measure
differentiate to
predict a
criterion
variable
currently
Analysis –
Correlation
Convergent Discriminant
Do the two
instruments
measuring the
concept
correlate
highly?
Does the
measure have
low correlation
with an
unrelated
variable?

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Data Source: SamplingData Source: Sampling
Two Central QuestionsTwo Central Questions
Do weDo we samplesample oror censuscensus??
If sample:If sample:

How to identifyHow to identify Who/whatWho/what to include into include in
the sample? - sampling designthe sample? - sampling design

HowHow manymany to include in the sample? -to include in the sample? -
sample sizesample size

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What is a Good Sample?What is a Good Sample?
RepresentativeRepresentative of the Populationof the Population
Estimates from sample areEstimates from sample are accurateaccurate
Estimates from sample areEstimates from sample are preciseprecise

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Steps in Sampling DesignSteps in Sampling Design
What is the relevantWhat is the relevant populationpopulation??
 What are theWhat are the parametersparameters of interest?of interest?
 What is theWhat is the sampling framesampling frame??
 WhatWhat sizesize sample is needed?sample is needed?
 What is theWhat is the typetype of sample?of sample?
 How much will itHow much will it costcost??

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Types of SamplingTypes of Sampling
DesignDesign
Non-
probability
Design
Probability
Design
Convenience
Judgement
Quota
Snowball
Simple Random
Systematic
Stratified
Cluster
Simple Random
Stratified
Combination
Sampling
Design
One-stage design
Multistage design

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Choosing a SamplingChoosing a Sampling
DesignDesign
Is REPRESENTATIVENESS critical?
Area
samples
Only experts
have
information
Info from
special
interest
groups
QuotaJudgement
Quick,
unreliable
information
Relevant
information
about certain
groups
Convenience
Simple
random
Systematic
Cluster if not
enough RM
Double
samples
Equal sized subgroups?
Proportionate
stratified samples
Disproportionate
stratified samples
YES NO
Choose PROBABILITY design Choose NON-PROBABILITY design
NOYES
Generaliza
bility
Subgroup
Differences
Collect
localized
information
Information
about
subsets of
sample

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Sample Size: FactorsSample Size: Factors
HomogeneityHomogeneity of sampling unitsof sampling units
ConfidenceConfidence levellevel
PrecisionPrecision
Analytical ProcedureAnalytical Procedure
Cost, Time and PersonnelCost, Time and Personnel

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Roscoe’s Rule of ThumbRoscoe’s Rule of Thumb
Larger than 30 and less than 500Larger than 30 and less than 500
appropriate for most researchappropriate for most research
A minimum of 30 for each sub samplesA minimum of 30 for each sub samples
Multivariate research: At least 10 timesMultivariate research: At least 10 times
the number of variablesthe number of variables
Simple Experiments with tight controlsSimple Experiments with tight controls
- samples as small as 10 to 20- samples as small as 10 to 20

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Types of Primary DataTypes of Primary Data
Collection MethodCollection Method
Data Collection Method
Passive Active
Disguised/
Undisguised
Structured/
Unstructured
Human/
Mechanical
Disguised/
Undisguised
Structured/
Unstructured
•Personal
•Telephone
•Mail
•Mechanical

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Personal InterviewPersonal Interview
Major concerns:Major concerns:

Non-responseNon-response

Response errorsResponse errors
Non-responseNon-response

Call-back, prior introduction, specific timesCall-back, prior introduction, specific times
Response BiasResponse Bias

Interview variations (situations, interviewer)Interview variations (situations, interviewer)

Question structuring & sequence (protocol)Question structuring & sequence (protocol)

Method of administration (socially accepted)Method of administration (socially accepted)

Respondent error (intentional and unintentional)Respondent error (intentional and unintentional)

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The InterviewThe Interview
IntroductionIntroduction

Establishes rapportEstablishes rapport
Gather DataGather Data

Probing (brief assertion of understanding,Probing (brief assertion of understanding,
expectant pause, repeating the question,expectant pause, repeating the question,
repeating the answer, neutral comment,repeating the answer, neutral comment,
question clarification)question clarification)
Recording the InterviewRecording the Interview

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Self-Administered SurveySelf-Administered Survey
TypeType

Intercept StudyIntercept Study

Mail surveyMail survey
DisadvantagesDisadvantages

Large non-response errorLarge non-response error

Superficial dataSuperficial data
Improving Response RateImproving Response Rate

Reduced length; survey sponsorship, return envelope,Reduced length; survey sponsorship, return envelope,
return postage, personalization, anonymity, size colorreturn postage, personalization, anonymity, size color
and reproduction, deadline dates, cover lettersand reproduction, deadline dates, cover letters

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Data Analysis – The StagesData Analysis – The Stages
InterpretationInterpretation
PreanalyticalPreanalytical
•Data Editing
•Variable Development
•Data Coding
•Error Check
Data AnalysisData Analysis
•Feel for Data
•Goodness of Measures
•Inferential: Testing & Relationships

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Data Analysis - TypesData Analysis - Types
Number of VariablesNumber of Variables
Univariate; Bivariate; MultivariateUnivariate; Bivariate; Multivariate
Level of MeasurementsLevel of Measurements
Nominal, Ordinal, Interval & RatioNominal, Ordinal, Interval & Ratio
Purpose of StudyPurpose of Study
Exploratory; Test of Differences;Exploratory; Test of Differences;
Establishing RelationshipsEstablishing Relationships

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The Right Technique?The Right Technique?
Number of VariablesNumber of Variables
Univariate; Bivariate; MultivariateUnivariate; Bivariate; Multivariate
Level of MeasurementsLevel of Measurements
Parametric and Non-parametricParametric and Non-parametric
Research QuestionResearch Question
Concern for Central Tendency;Concern for Central Tendency;
Comparing groups; RelationshipsComparing groups; Relationships

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The Right Technique?The Right Technique?
What is the purpose of the analysis?What is the purpose of the analysis?
What is the level of measurement?What is the level of measurement?
How many variables are involved?How many variables are involved?

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Descriptive AnalysisDescriptive Analysis
TechniquesTechniques
Frequencies Distribution - if 1 ordinal orFrequencies Distribution - if 1 ordinal or
nominal variable,nominal variable,
Cross-tabulation - if 2 ordinal or nominalCross-tabulation - if 2 ordinal or nominal
variablesvariables
Means - if 1 interval or ratio level variableMeans - if 1 interval or ratio level variable
Means of subgroups - if 1 interval or ratioMeans of subgroups - if 1 interval or ratio
level variable by subgroupslevel variable by subgroups
PurposePurpose:: To describe the distribution of theTo describe the distribution of the
variables of interestvariables of interest

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Test of DifferencesTest of Differences
TechniquesTechniques depends ondepends on
Levels of Measurement of the VariableLevels of Measurement of the Variable
Number of GroupsNumber of Groups
Independence of the GroupsIndependence of the Groups
PurposePurpose:: To evaluate the differencesTo evaluate the differences
between 2 or more groups with respect to abetween 2 or more groups with respect to a
variable of interestvariable of interest

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Test of DifferencesTest of Differences
More than 2
group?
Are they
independent
?
Are they
independent
?
Nominal: χ2-
test
Ordinal:
Mann-Whitney
Continuous: t-
test
Yes
Nominal:
McNemar
Ordinal: Wilcoxon
Signed Rank
Continuous:-
Paired t-test
No
No Yes
Nominal: χ2
test
Ordinal: Kruskal-
Wallis ANOVA
Continuous: 1-way
ANOVA
Nominal: χ2
- test
Ordinal: Friedman
2-way ANOVA
Continuous:
Factorial 2-way
ANOVA

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RelationshipRelationship
TechniquesTechniques depends ondepends on
Whether or not there exist dependentWhether or not there exist dependent
variable(s)variable(s)
Number of dependent and independentNumber of dependent and independent
variablesvariables
Levels of Measurement of the VariableLevels of Measurement of the Variable
PurposePurpose:: To establish relationshipTo establish relationship
between variablesbetween variables

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DependenceDependence
RelationshipsRelationshipsHow many
dependent
variables?
Scale of
Dependent
Multiple
Regression
ANOVA Discriminant
Analysis
Canonical
Correlation
Scale of
Independe
nt
Scale of
Dependent
Scale of
Independen
t
Multivariate
ANOVA
More than 1
One
Conjoint
Analysis
Scale of
independen
t
Interval
Nominal
Interval Nominal
Scale of
Independe
nt
Interval Nominal
Interval

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Contents of a ResearchContents of a Research
ProposalProposal
Data preparationData preparation
A brief description of researchA brief description of research
methodologymethodology
Data collectionData collection
Data analysis and interpretationData analysis and interpretation
Research reportingResearch reporting
A statement of the research problemA statement of the research problem

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Final WordsFinal Words
Good Luck in Your
Research and Remember
the Good Research begins
with an Inquisitive Mind