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Normality Tests

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Normality Tests - Tests of whether a set of data is distributed in a way that is consistent with a Normal Distribution. Typically, they are tests of a Null Hypothesis that the data are drawn from a Normal Population, specifically a Goodness-Of-Fit Test. Hence, while it is possible to reach a definitive conclusion that a set of data is not normally-distributed (by rejecting the null hypothesis), the most one can say if the null hypothesis is not rejected is that the data could possibly come from a normally distributed population. See Lilliefors Test for normality.