Skewness is a measure of the degree of asymmetry of a distribution. If the left(tail at small end of the distribution) is more pronounced than the right tail (tail at the large end of the distribution), the function is said to have skewness. If the reverse is true, it has skewness. If the two are equal, it has zero skewness.
Several types of skewness are defined, the terminology and notation of which are unfortunately rather confusing. "The" skewness of a distribution is defined to be
Nagatively Skewed Distribution: - If the value of the mode is greater than the arithmetic mean; the distribution is called Negatively Skewed.
Several forms of skewness are also defined. Theis defined by
Theis defined by
are defined by
The(also known as quartile skewness coefficient) is defined by
where the s denote the. The is