Selection of appropriate statistics and tools

Selection of Appropriate Statistics
and Tools
Dr. Suresh Kumar Murugesan PhD

About the Presenter
● Dr.Suresh Kumar Murugesan is a passionate Professor, researcher and
Mental Health Practitioner from Madurai, Tamil Nadu, India
● At present he is Heading the department of Psychology, The
American College, Madurai and Adjunct Professor of School of
Behavioural Sciences and Education at TAU
● He is the State President of World Congress of Psychologists (WCOP)
and he is very keen in learning new research studies in behavioural
Sciences and open to learn.
● His ultimate aim is to make impression in the field of Knowledge
● His area of specializations are Psychometry, Counselling &
Psychotherapy, Positive Psychology, Education Psychology.

Disclaimer
This presentation is prepared for
learning purpose only and all the
images and pictures used in this
presentation are taken from
google image search.
Due recognition was given to all
the material collected from the
various sources.
Any name or reference is missed
kindly bring it to the notice of the
presenter for inclusion.
Email -
sureshkumar800@yahoo.com
Thank you

WHICH LIST CORRECT? WHY?
LIST - A
1. 1, ii, 3, four, v, 6…..
2. I, 2, III, iv, 5, six….
3. 1, 2, 3, 4, v, 6….
4. i, ii, 3, 4, v, VI….
LIST - B
1. 1, 2, 3, 4, 5, 6 ……
2. i, ii, iii, iv, v, vi……
3. I, II, III, IV, V, VI…..
4. ONE, TWO, THREE, FOUR,
FIVE,….

NAME SOME OF THE STATISTICAL
TOOLS

STATISTICAL TOOLS AND
TECHNIQUES
1. Parametric
2. Non- Parametric

WHY STATISTICS IN
RESEARCH?
1. Statistical methods involved in carrying out a study
include planning, designing, collecting data, analysing,
drawing meaningful interpretation and reporting of the
research findings.
Statistics
Planning
Designing
Collecting Data
Analyzing
Drawing Meaningful
Interpretation
Reporting

WHY STATISTICS IN
RESEARCH?
1. The statistical analysis gives meaning to the meaningless
numbers, thereby breathing life into a lifeless data.
2. The results and inferences are precise only if proper
statistical tests are used.

FEW MORE QUESTIONS ?????
(VARIABLE)
Which statistical technique will you use? Why?
1. To find out the influence of one variable on other variable
2. To find out the association between variables
3. To find our the relationship between two variables?
4. To find out the level of study variable

(SAMPLE)
1. If the sample size is less than 10
2. For random sample
3. Non random sample
4. Homogeneous sample and heterogeneous sample

(SCALES)
1. For ratio scale data
2. For interval scale data
3. For ordinal scale data
4. For nominal scale data

When to Use
Parametric
1. When the distribution is normal
2. Large Sample
3. Interval and Ratio distributions
4. Random sampling
5. When decided to make an
assumptions
Nonparametric
1. when the distribution is not
normal
2. Small Sample
3. Nominal and ordinal distribution
4. Non Random sampling
5. When it is not make an
assumptions
Dr. Suresh Kumar Murugesan PhD, +91 790486 5059 sureshkumar800@yahoo.com

Types of Data

NPC

Scales of Measurement

TYPES OF STATISTICAL
ANALYSIS
Dr. Suresh Kumar
Murugesan PhD
+91 7904865059
sureshkumar800@yahoo.co
m
Madurai, Tamil Nadu, India
Madurai, Meenakshi Amman Temple

LEARNING OUTCOME
At the end of the session the learners will be able to understand and apply in
their field
1. Types of statistical Analysis
�Descriptive Data Analysis
�Inferential Statistical Analysis
�Difference Statistical Analysis
�Association Statistical Analysis
�Predictive Statistical Analysis
2. When to use parametric and non parametric?

Types of Statistical Analysis
Dr. Suresh Kumar Murugesan PhD +91 790486 5059 sureshkumar800@yahoo.com

TYPES OF STATISTICAL
ANALYSIS
Types
of
Statistical
Analysis
Descriptive What are the characteristics of the respondents?
Inferential What are the characteristics of the population?
Differences Are two are more groups same or different?
Association Are two or more variables related in a systematic way?
Predictive
Can we predict one variable if we know one or more
other variables in the study?

Descriptive Analysis

Descriptive
Statistical
Analysis
Tables Frequency Distribution
Graphs
Bar Diagram
Pie Diagram
Line Graph
Histogram
Numbers
Centre Mean, Median, Mode
Important Points
Median, Quartiles,
Deciles, Percentiles
Variation
Range, Variance,
Standard Deviation
Distribution
Skewness and
Kurtosis

Descriptive Analysis - Tables

EXAMPLE -1
Simple Table Crosstabulation

EXAMPLE -2

Descriptive Analysis - Graphs

GRAPHS – EXAMPLE 1
Bar Diagram Histogram Diagram

GRAPHS – EXAMPLE 2
Line Graph Pie Diagram

Descriptive Analysis – Numbers (Centre)

EXAMPLE – MEAN, MEDIAN
AND MODE

Descriptive Analysis – Numbers (Important
Points)

EXAMPLE MEDIAN AND
QUARTILE
Median Quartile

EXAMPLE FOR PERCENTILE

EXAMPLE FOR DECILE

Descriptive Analysis – Numbers (Variance)

Example of samples from two populations with the same mean but different dispersion.
The blue population is much more dispersed than the red population.

EXAMPLE - RANGE

EXAMPLE – STANDARD
DEVIATION

EXAMPLE – VARIANCE

Descriptive Analysis – Numbers
(Distribution)

EXAMPLE FOR SKEWNESS
AND KURTOSIS

Skewness Kurtosis

What is Inferential Statistics?

INFERENTIAL STATISTICS

Population
Sample
Conclusion
based on
Sample
Hypothesis

Descriptive Vs inferential Statistics

Differences Statistical Analysis

Differences Statistical Analysis
Parametric
Paired ‘t’ Test
Unpaired ‘t’ Test
‘F’ Test
Non- Para metric
Wilcoxon Rank sum
test
Mann-Whitney U test
Kruskal Wallis Test

Association Statistical Analysis

Association Statistical Analysis
Parametric
Product moment Order
Correlation
Non- Para metric
Rank Order Correlation

Predictive Statistical Analysis

Predictive
Statistical
Analysis
Parametric/ Non-
Para metric
Regression
Analysis
Discriminant
Function
Analysis

When to Use Parametric or Non parametric
Statistics?

WHEN TO USE?
Parametric
1. Decided to make assumption about
the Population
2. Probabilistic distribution is normal
3. Sampling is based on probability or
randomness
4. Data collected on the scale of
interval or ratio
5. Large Sample size
6. Homogeneous data
7. Independent data set
Non Parametric
1. Don’t make assumption but describe
2. Distribution is arbitrary or not normal
3. Sampling is non probability or non
randomness
4. Data collected on the scale of
nominal or interval
5. Small Sample size
6. Homogeneous and Heterogeneous
data
7. Any data set

UNDERSTANDING THE TERMS IN
STATISTICS

Thank you

Contact Dr. Suresh Kumar Murugesan PhD
sureshkumar@americancollege.edu.in
7, Vivekananda Street,
New Vilangudi,
Madurai, Tamil Nadu, India
+91 9750 406463

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