*Choose Index below for a list of all words and phrases defined in this glossary.*

**skewness** - 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.

In a normal distribution, the graph appears as a classical, symmetrical "bell-shaped curve." The mean, or average, and the mode, or maximum point on the curve, are equal.

* In a perfect normal distribution (green solid curve in the illustration below), the tails on either side of the curve are exact mirror images of each other. * When a distribution is skewed to the left (red dashed curve), the tail on the curve's left-hand side is longer than the tail on the right-hand side, and the mean is less than the mode. This situation is also called negative skewness. * When a distribution is skewed to the right (blue dotted curve), the tail on the curve's right-hand side is longer than the tail on the left-hand side, and the mean is greater than the mode. This situation is also called positive skewness.

[Category=Data Management ]

*Source: WhatIs.com, 08 September 2013 09:00:57, http://whatis.techtarget.com/glossary/Data-and-Data-Management *

Data Quality Glossary. A free resource from GRC Data Intelligence. For comments, questions or feedback: dqglossary@grcdi.nl