Non-Normal Distributions

A statistical distribution that reflects non-normal or atypical randomness in the spread of data points around the central tendency. This distribution doesn't look like the typical "bell curve" of a normal distribution, but may reflect an asymmetrical spread of more than 50% of the data points on just one side of the mean (i.e., the average or center of the distribution). Very often this uneven spread will appear like a tall peak of data points on one side and a long tail of remaining data points stretching across the other side of the bottom of the scale. A long tail forming to the right is a positive skew and a long tail of data points forming to the left is a negative skew. This non-normality implies there is bias or skewness (i.e., non-normality) in the data. The non-normality of a distribution may appear visually obvious but it should be statistically validated such as in using an Anderson-Darling (AD) test of a Normality Test or Probability Plot.
Related StatStuff Videos: 
   -Section 5-Measure Phase, Lesson #8 - Distributions: Overview
   -Section 5-Measure Phase, Lesson #10 - Distributions: Non-Normal