Bowley’s Coefficient of Skewness
Bowley’s Coefficient of Skewness is a statistical measure that helps determine the skewness or asymmetry of a data distribution. It is particularly useful for identifying the direction and degree of skewness in a dataset. Unlike other measures of skewness that rely on mean and standard deviation, Bowley’s method uses quartiles, making it robust against outliers.
Bowley’s Coefficient Formula
Bowley’s Coefficient of Skewness is calculated using the following formula:
Bowley’s Coefficient = (Q3 – Q2) – (Q2 – Q1)/(Q3 – Q1)
OR
Bowley’s Coefficient = (Q3 + Q1 – 2Q2) /(Q3 – Q1)
Where,
- Q1 is the first quartile (25th percentile)
- Q2 is the second quartile (median or 50th percentile)
- Q3 is the third quartile (75th percentile)
Coefficient of Skewness
Coefficient of Skewness is a statistical measure that indicates the asymmetry of data around its mean, revealing whether the data is skewed to the left, right, or is symmetrical.
By identifying the direction and degree of skewness, researchers can gain insights into the underlying patterns and characteristics of the data. In this article, we will discuss all the Coefficient of Skewness i.e., Pearson’s Coefficient, Bowley’s Coefficient, and Kelly’s Coefficient.
Table of Content
- What is Skewness?
- Types of Skewness
- What is Coefficient of Skewness?
- Pearson’s First Coefficient of Skewness
- Pearson’s Second Coefficient of Skewness
- Bowley’s Coefficient of Skewness
- Kelly’s Coefficient of Skewness
- Interpreatation of Coefficient of Skewness
- FAQs