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  2. Normality test - Wikipedia

    en.wikipedia.org/wiki/Normality_test

    The energy and the ECF tests are powerful tests that apply for testing univariate or multivariate normality and are statistically consistent against general alternatives. The normal distribution has the highest entropy of any distribution for a given standard deviation. There are a number of normality tests based on this property, the first ...

  3. Shapiro–Wilk test - Wikipedia

    en.wikipedia.org/wiki/Shapiro–Wilk_test

    The Shapiro–Wilk test tests the null hypothesis that a sample x 1, ..., x n came from a normally distributed population. The test statistic is = (= ()) = (¯), where with parentheses enclosing the subscript index i is the ith order statistic, i.e., the ith-smallest number in the sample (not to be confused with ).

  4. Shapiro–Francia test - Wikipedia

    en.wikipedia.org/wiki/Shapiro–Francia_test

    The Shapiro–Francia test is a statistical test for the normality of a population, based on sample data. It was introduced by S. S. Shapiro and R. S. Francia in 1972 as a simplification of the Shapiro–Wilk test .

  5. Normal probability plot - Wikipedia

    en.wikipedia.org/wiki/Normal_probability_plot

    Normal probability plots are made of raw data, residuals from model fits, and estimated parameters. A normal probability plot. In a normal probability plot (also called a "normal plot"), the sorted data are plotted vs. values selected to make the resulting image look close to a straight line if the data are approximately normally distributed.

  6. Anderson–Darling test - Wikipedia

    en.wikipedia.org/wiki/Anderson–Darling_test

    The Anderson–Darling test assesses whether a sample comes from a specified distribution. It makes use of the fact that, when given a hypothesized underlying distribution and assuming the data does arise from this distribution, the cumulative distribution function (CDF) of the data can be transformed to what should follow a uniform distribution.

  7. Lilliefors test - Wikipedia

    en.wikipedia.org/wiki/Lilliefors_test

    Lilliefors test is a normality test based on the Kolmogorov–Smirnov test.It is used to test the null hypothesis that data come from a normally distributed population, when the null hypothesis does not specify which normal distribution; i.e., it does not specify the expected value and variance of the distribution. [1]

  8. Jarque–Bera test - Wikipedia

    en.wikipedia.org/wiki/Jarque–Bera_test

    In statistics, the Jarque–Bera test is a goodness-of-fit test of whether sample data have the skewness and kurtosis matching a normal distribution. The test is named after Carlos Jarque and Anil K. Bera. The test statistic is always nonnegative. If it is far from zero, it signals the data do not have a normal distribution.

  9. Category:Normality tests - Wikipedia

    en.wikipedia.org/wiki/Category:Normality_tests

    It should only contain pages that are Normality tests or lists of Normality tests, as well as subcategories containing those things (themselves set categories). Topics about Normality tests in general should be placed in relevant topic categories .