What is "normality"?
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Revision as of 20:54, 7 September 2009 by Doug
- What is "normality"?
- A normal distribution is a symmetric bell-shaped curve defined by two things: the mean (average) and variance (variability). There are an infinite number of normal distributions because there are an infinite number of permutations of the mean and variance.
- Most statistical tests rest upon the assumption of normality. Deviations from normality, called non-normality, render those statistical tests inaccurate, so it is important to know if your data are normal or non-normal.
- - To provide a rough example of normality and non-normality, see the following histograms. The black line superimposed on the histograms represents the bell-shaped "normal" curve. Notice how the data for variable1 are normal, and the data for variable2 are non-normal. In this case, the non-normality is driven by the presence of an outlier. For more information about outliers, see What are outliers?, How do I detect outliers?, and How do I deal with outliers?.
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