This Powerpoint Presentation has been made while referring to the research books written by eminent, renowned and expert authors as mentioned in the references section. The purpose of this Presentation is to help the research students in developing an insight about the Data Analysis in Research. I hope the students will find this presentation useful for them. All the best Dr. Shaloo Saini

1. Understanding The Data Analysis
(Part-I)
By
Dr. Shaloo Saini
Assistant Professor
MKCE, C T Group of Institutions, Jalandhar Punjab

2. Data Analysis
Data Analysis refers to the use of statistical techniques to order the data with the objective of obtaining the answers to the research questions.
Data Analysis can be viewed as the ordering, the breaking down into constituent parts and the manipulation of data to obtain answer to the research
questions underlying the research project(Kerlinger,1964)
Analysis of Data is done by using a careful plan, developed by an open minded and flexible analyst.
Good,Bar and Scales(1941) have stated the four modes to begin the Data Analysis:
1. To think in terms of significant tables that the data permits.
2. To examine carefully the statement of problem and earlier analysis and to study the original records of data.
3. To get away from the data and to think about the problem in layman’s terms or to actually discuss the problems with others.
4. To attack the data by making various statistical calculations.

3. Factors Influencing Data Analysis Strategy
I: Type of Data
II: Research Design
III: Researcher’s Qualification
IV: Assumptions Underlying a Technique

4. I: Type of Data
1 Nominal Data If the Data is Nominal then Mode and Some Non Parametric
tests can be applied for Data Analysis
2 Ordinal Data If the Data is ordinal then Median, Mode and Some Non
Parametric Tests can be applied for Data Analysis
3 Interval Data If the Data is Interval then all the Descriptive Statistics,
Parametric Tests and Non Parametric Tests can be applied for
Data Analysis
4 Ratio Data If the Data is Ratio then all the Descriptive Statistics, Parametric
Tests and Non Parametric Tests can be applied for Data
Analysis

5. Recommended Statistical Techniques by Measurement Level
and Testing Situation( Cooper, Schindler,Sharma,2012,p542)
Measure
ment
Scale
One Sample
Test
Two Samples Test K Samples Test
Related
Samples
Independent Samples Related
Samples
Independent
Samples
Nominal 1.Binomial
2.Chi Square
one sample test
1.Mc Nemar 1.Fisher Exact Test
2.Chi Square two
Samples Test
1.Cochran Q 1.Chi Square for
K samples
Ordinal 1.Kolmogorov-S
mirnov one
sample test
2.Runs test
1.Sign Test
2.Wilcoxon
matched
Pairs test
1.Median Test
2.Mann-Whitney U test
3.Kolmogorov-Smirnov
4.Wald-Wolfowitz test
1.Friedman
two way
ANOVA
1.Median
Extension
2.Kruskal Wallis
one way ANOVA
Interval
and Ratio
1.t- test
2.z- test
1.t test for
paired
samples
1.t- test
2.z- test
1.Repeated
Measures
ANOVA
1.One Way
ANOVA
2.n way ANOVA

6. II: Research Design
The Research Design is another important factor that influence the decision related to the selection of the
appropriate Data Analysis Strategy. The decision is based on the:
● Number of Variables being observed in the research
● Sample dependence and independence
● Number of observations per subject
● Number of Groups and sub groups formed
In case of Single variable being observed the Univariate Techniques are applied for the Data Analysis whereas
for more than one variable the Bivariate/ Multivariate Techniques are applied for the Data Analysis

7. Univariate Statistical Techniques
(Bajpai,2011,p201)
Metric Data(Parametric Tests) Non Metric Data(Non Parametric Tests)
One
Sample
Test
Two or More Samples Test One Sample
Test
Two or More Samples Test
1.T Test
2.Z test
Dependent
Samples
Independent
Samples
Dependent Samples Independent Samples
1.Paired T
Test
1.T test for two
population
2.Z test for two
population
3.One way
1.Chi Square
Test
2.Run’s Test
3.Kolmogorov-
Smirnov
1.Wilcoxon matched
Pairs Test
2.Sign Test
3.Mc Nemar Test
4.Chi Square Test
1.Chi Square Test
2.Mann Whitney U Test
3.Kolmogorov Smirnov
test
4.Kruskal Wallis Test

8. Multivariate Statistical Techniques
(Bajpai,2011,p202)
Dependence Techniques Interdependence Techniques
One Dependent Variable Several Dependent Variables
Metric Data Non Metric Data Metric Data Non Metric
Data
Metric Data Non Metric
Data
1.ANOVA
2.ANCOVA
3.Multiple
Regression
4.Conjoint
Analysis
1.Multiple
Discriminant
Analysis
1.MANOVA
2.MANCOVA
Canonical
Correction
1.Factor
Analysis
2.Cluster
Analysis
3.Metric
Multidimensional
Scaling
1.Non Metric
Scaling
2.Latent
Structural
Analysis

9. III: Researcher’s Qualification
The Experience, Qualifications, Philosophy, Capability and confidence of the Researcher are also the
important factors in determining the Data analysis strategies.
The Researcher who has these qualities will not hesitate to employ a wide variety of sophisticated statistical
techniques whereas the researcher who are hesitant and lack expertise in statistical techniques applications
will opt for simpler ways of analysing the data.

10. IV: Assumptions Underlying A Technique
Use of statistical techniques are based on certain assumptions.A particular statistical technique can only be
employed if its fulfills certain assumptions specifying their usages.
Eg: “t” text can be applied only when the sample is independent and small in size and has been drawn from a
population having normal distribution.

11. Summary
The process of converting Raw Data into information starts with the Data Processing and continues to Data
Analysis. The Data analysis is done by applying various statistical techniques available however the decision
regarding the appropriate techniques to employed depends upon certain factors. These factors are Type of
Data, Research Design, Researchers qualifications and the assumptions underlying the use of statistical
technique. The interpretation of the data and finding the answer to research questions depends upon the
correctness of the data analysis. Therefore Data analysis should be precisely done and expert help should be
taken whenever needed.

12. References
Bajpai N. (2015). Fieldwork and Data Preperation. In Business research methods (pp. 201-202). Nodia:
Pearson Education.
Good C.V., Barr A.S. & Scates D.E.(1941). Methodology of Educational Research (pp. 599-601).
Appleton Crofts Inc, New York.
Gupta S.K. & Rangi P.(2017). Data Analysis. In Research Methodology (4
th
ed., pp10.1-10.45).Punjab:
Kalyani Publishers(India).
Kerlinger F.N.(1964). Foundations of Behavioural Research, Holt,Rinehart and Winston(p.103), New
York.
Kothari C. R. & Garg G.(2019). Data Preperation. In Research Methodology Methods and Techniques(
4
th
ed., pp.114-128) New Delhi: New Age International Publishers(India).

13. Thank You
This Powerpoint Presentation has been made while referring to the
research books written by eminent, renowned and expert authors as
mentioned in the references section. The purpose of this Presentation is
to help the research students in developing an insight about the Data
Analysis in Research. I hope the students will find this presentation
useful for them.
All the Best
Dr. Shaloo Saini