Distributions which are approximately normal are frequently encountered, e.g. most sets of random errors follow the normal distribution.
The normal distribution is important as a ‘limiting distribution’, i.e. it can be used as an approximation to other distributions (see sections 8.7 and 8.8).
The normal distribution is easy to use.
It has been shown that the results obtained by assuming a non-normal population to be normally distributed are reasonably accurate when the departure from normality is not too severe.
The central limit theorem shows that the means of samples of size n from any population are approximately normally distributed. The approximation improves as n gets bigger.
KeywordsNormal Distribution Poisson Distribution Binomial Distribution Normal Approximation Normal Curve
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