Pearson’s First Coefficient of Skewness
Pearson’s First Coefficient of Skewness is a measure of skewness that compares the mean and the mode of a data distribution. Pearson’s First Coefficient of Skewness, also known as the moment coefficient of skewness, is one of the most widely used measures of skewness. It is used to determine the direction and extent of the skewness in the data.
Pearson’s First Coefficient Formula
Pearson’s First Coefficient of Skewness is calculated using the following formula:
Pearson’s First Coefficient Formula = (Mean – Mode)/Standarad Deviation
Where,
- Mean is the average value of the dataset.
- Mode is the most frequently occurring value in the dataset.
- Standard Deviation is a measure of the amount of variation or dispersion in the dataset.
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