Skewness Meaning. 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. The skewness value can be positive zero negative or undefined.
Skewness can be quantified to define the extent to which a distribution differs from a normal distribution. Skewness describes how much statistical data distribution is asymmetrical from the normal distribution where distribution is equally divided on each 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.
In a normal distribution the graph appears as a classical symmetrical bell shaped curve.
Skewness refers to distortion or asymmetry in a symmetrical bell curve or normal distribution in a set of data. 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. In a normal distribution the graph appears as a classical symmetrical bell shaped curve. If the curve is shifted to the left or to the right it is said to be skewed.
