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PPT - Bowley’s Coefficient of Skewness, B Com Notes | EduRev

B Com : PPT - Bowley’s Coefficient of Skewness, B Com Notes | EduRev

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Presentation On
Concept of Skewness:
Bowley’s Method
Page 2

Presentation On
Concept of Skewness:
Bowley’s Method
OVERVIEW
? Introduction: Skewness
? Symmetric Distribution
? Two types of skewness
? Measure of Skewness: Bo w ley ’ s Method
? Illustration
? Verification
? Conclusion
Page 3

Presentation On
Concept of Skewness:
Bowley’s Method
OVERVIEW
? Introduction: Skewness
? Symmetric Distribution
? Two types of skewness
? Measure of Skewness: Bo w ley ’ s Method
? Illustration
? Verification
? Conclusion
INTRODUCTION: SKEWNESS
?Measure of lack of symmetry
?Absence of symmetry
?Extreme values in either side of a distribution
?If the two sides do not coincide, distribution is said to be
asymmetric
?A distribution that is asymmetric with respect to a
vertical axis is said to be skewed.
Page 4

Presentation On
Concept of Skewness:
Bowley’s Method
OVERVIEW
? Introduction: Skewness
? Symmetric Distribution
? Two types of skewness
? Measure of Skewness: Bo w ley ’ s Method
? Illustration
? Verification
? Conclusion
INTRODUCTION: SKEWNESS
?Measure of lack of symmetry
?Absence of symmetry
?Extreme values in either side of a distribution
?If the two sides do not coincide, distribution is said to be
asymmetric
?A distribution that is asymmetric with respect to a
vertical axis is said to be skewed.
SYMMETRIC DISTRIBUTION
?A distribution is symmetric if it can be folded along the
vertical axis so that the two side coincide
?If the distribution is symmetric, the mean, the median, and
the mode are equal and are located at the same position along
the horizontal axis
FIGURE 1a.  Example of a Symmetric
Distribution
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9
mean = median = mode
No. of Provinces
Page 5

Presentation On
Concept of Skewness:
Bowley’s Method
OVERVIEW
? Introduction: Skewness
? Symmetric Distribution
? Two types of skewness
? Measure of Skewness: Bo w ley ’ s Method
? Illustration
? Verification
? Conclusion
INTRODUCTION: SKEWNESS
?Measure of lack of symmetry
?Absence of symmetry
?Extreme values in either side of a distribution
?If the two sides do not coincide, distribution is said to be
asymmetric
?A distribution that is asymmetric with respect to a
vertical axis is said to be skewed.
SYMMETRIC DISTRIBUTION
?A distribution is symmetric if it can be folded along the
vertical axis so that the two side coincide
?If the distribution is symmetric, the mean, the median, and
the mode are equal and are located at the same position along
the horizontal axis
FIGURE 1a.  Example of a Symmetric
Distribution
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9
mean = median = mode
No. of Provinces
TWO TYPES OF SKEWNESS
Positively Skewed or Skewed to the Right
Distribution
? Distribution tapers more to the right than to the
left
? Has a longer tail to the right compared to a much
shorter left tail
? Values are more concentrated below than above the
mean
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