Statistics Tips

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

2. 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,Positive Psychology

3. 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

4. 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,….

5. WHAT IS TOOL?
List 1 List 2

6. NAME SOME OF THE STATISTICAL TOOLS

7. WHAT IS STATISTICAL TOOL?

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

9. 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

10. 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.

11. 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
●

12. FEW MORE QUESTIONS ????? (SAMPLE)
Which statistical technique will you use? Why?
1. If the sample size is less than 10
2. For random sample
3. Non random sample
4. Homogeneous sample and heterogeneous sample
●

13. FEW MORE QUESTIONS ????? (SCALES)
Which statistical technique will you use? Why?
1. For ratio scale data
2. For interval scale data
3. For ordinal scale data
4. For nominal scale data
●

14. What is Statistics?

15. WHAT IS STATISTICS?

16. Population Vs Sample

18. Parameter Vs Statistics

21. Parametric Vs Nonparametric

22. 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

32. Types of Data

34. NPC

36. Scales of Measurement

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

45. 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?

46. Types of Statistical Analysis

47. 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?

48. Descriptive Analysis

49. 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

50. Descriptive Analysis - Tables

51. EXAMPLE -1
Simple Table Cross Tabulation

52. EXAMPLE -2

53. Descriptive Analysis - Graphs

55. GRAPHS – EXAMPLE 1
Bar Diagram Histogram Diagram

56. GRAPHS – EXAMPLE 2
Line Graph Pie Diagram

57. Descriptive Analysis – Numbers (Centre)

58. EXAMPLE – MEAN, MEDIAN AND MODE

60. Descriptive Analysis – Numbers (Important Points)

61. EXAMPLE MEDIAN AND QUARTILE
Median Quartile

62. EXAMPLE FOR PERCENTILE

63. EXAMPLE FOR PERCENTILE

64. EXAMPLE FOR DECILE

65. Descriptive Analysis – Numbers (Variance)

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

67. EXAMPLE - RANGE

68. EXAMPLE – STANDARD DEVIATION

69. EXAMPLE – VARIANCE

70. Descriptive Analysis – Numbers (Distribution)

71. EXAMPLE FOR SKEWNESS AND
KURTOSIS

72. Skewness Kurtosis

73. What is Inferential Statistics?

74. INFERENTIAL STATISTICS

75. Population
Sample
Conclusion based
on Sample
Hypothesis

77. Descriptive Vs inferential Statistics

81. Differences Statistical Analysis

82. 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

83. Association Statistical Analysis

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

85. Predictive Statistical Analysis

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

87. When to Use Parametric or Non parametric
Statistics?

90. 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

91. UNDERSTANDING THE TERMS IN
STATISTICS

92. Thank you