This document discusses skewness and measures of skewness in quantitative techniques. It begins with learning objectives to help students understand different measures of skewness and distinguish between normal and abnormal distributions. It then defines skewness as an asymmetrical or lack of symmetry in a frequency distribution. Measures of skewness are classified as absolute, using the difference between mean and mode, or relative, using the standard deviation. Relative measures discussed include Karl Pearson's, Bowley's, and Kelly's coefficients of skewness. Multiple choice questions are then provided as an assessment.
2. RECAP
• Combined Mean & Combined Standard Deviation
Typical Problems------------------------------ 02
3. LEARNING OBJECTIVES
• The aim of the chapter is to make students to
understand Measures of Skewness, Karl Pearson
Co-efficient of Skewness and Bowley's Co-efficient
of skewness
4. LEARNING OUTCOMES
• After this Unit The Students can be able to apply to
Sample Population Data by Differentiating Normal
and Abnormal Distributions with regard to
Dispersion & Skewness.
5. SESSION - 51
• Meaning & Definition of Skewness, Measures of
Skewness
6. SKEWNESS
• MEANING
When the data set is not a symmetrical distribution, it is
called a skewness and such a distribution could either be
positively skewed or negatively skewed.
• DEFINITION
CROXTON AND COWDEN “when a series is not
symmetrical it is said to be asymmetrical or Skewed”.
MORRIS HAMBURG “skewness refers to the asymmetric
or lack of symmetry in the shape of frequency
distribution”.
7. MEASURES OF SKEWNESS
Broadly classified the measures of Skewness are Two
types. They are
1. Absolute Measure
2. Relative Measure
Absolute Measure: it refers to difference between mean
and mode. SK = x- Z
Relative Measure; If we divide mean and mode
difference by the standard deviation we obtain a relative
measure of skewness known as the coefficient and
denoted by skewness.
8. CONTD
Relative Measures of skewness are
• Karl Pearson's Co-efficient of skewness
• Bowley’s Co-efficient of skewness
• Kelly’s Co-efficient of skewness
9. SUMMARY
As we already discussed and learnt today on skewness
as below
• Meaning & Definition of Skewness, Measures of
Skewness
10. MCQs
1 . In measures of skewness, the absolute skewness is
equal to
a) Mean + Mode
b) Mean – Mode
c) Mean + Median
d) Mean – Median
2. If mean is less than mode, the distribution will be
a) Positively skewed
b) Negatively skewed
c) Symmetrical
d) None of these
11. MCQs
3 . In symmetrical distribution, mean, median, and mode
are:
a) Equal
b) Different
c) Zero
d) None of these
4. If mean, median, and mode are all equal then
distribution will be
a) Positive Skewed
b) Negative Skewed
c) Symmetrical
d) None of these
12. MCQs
5 . The values of mean, median and mode can be
a) Some time equal
b) Never equal
c) Always equal
d) None of these
14. REFERENCES
• S.P. Gupta, Sultan Chand and Sons Publications, 2017
• S. C. Gupta, Himalaya Publishing House,
Fundamentals of Statistics, 2018
• R.S.N Pillai and Bagavathi, S.Chand publications, 2010