Lack of symmetry is called Skewness. If a distribution is not symmetrical then it is called skewed distribution. So, mean, median and mode are different in values and one tail becomes longer than other. The skewness may be positive or negative.

__Positively skewed distribution__:

If the frequency curve has longer tail to right the distribution is known as positively skewed distribution and ** Mean > Median > Mode**.

__Negatively skewed distribution__:

If the frequency curve has longer tail to left the distribution is known as negatively skewed distribution and ** Mean < Median < Mode**.

__Measure of Skewness__:

The difference between the mean and mode gives as absolute measure of skewness. If we divide this difference by standard deviation we obtain a relative measure of skewness known as coefficient and denoted by * SK*.

Karl Pearson coefficient of Skewness

Sometimes the mode is difficult to find. So we use another formula

Bowley’s coefficient of Skewness