Skewness Meaning. Skewness can be quantified to define the extent to which a distribution differs from a normal distribution. In a normal distribution the graph appears as a classical symmetrical bell shaped curve.
If a distribution is not symmetrical or normal then it is skewed i e it is either the frequency distribution skewed to the left side or to the right side. In probability theory and statistics skewness is a measure of the asymmetry of the probability distribution of a real valued random variable about its mean. Skewness is asymmetry in a statistical distribution in which the curve appears distorted or skewed either to the left or to the right.
Skewness can be quantified to define the extent to which a distribution differs from a normal distribution.
If a distribution is not symmetrical or normal then it is skewed i e it is either the frequency distribution skewed to the left side or to the right side. If the curve is shifted to the left or to the right it is said to be skewed. In a normal distribution the graph appears as a classical symmetrical bell shaped curve. In probability theory and statistics skewness is a measure of the asymmetry of the probability distribution of a real valued random variable about its mean.
