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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 ).
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Shapiro–Wilk test: interval: univariate: 1: Normality test: sample size between 3 and 5000 [16] Kolmogorov–Smirnov test: interval: 1: Normality test: distribution parameters known [16] Shapiro-Francia test: interval: univariate: 1: Normality test: Simpliplification of Shapiro–Wilk test Lilliefors test: interval: 1: Normality test
Kolmogorov–Smirnov test: this test only works if the mean and the variance of the normal distribution are assumed known under the null hypothesis, Lilliefors test: based on the Kolmogorov–Smirnov test, adjusted for when also estimating the mean and variance from the data, Shapiro–Wilk test, and; Pearson's chi-squared test.
Martin Bradbury Wilk, OC (18 December 1922 – 19 February 2013) [1] [2] was a Canadian statistician, academic, and the former chief statistician of Canada. In 1965, together with Samuel Shapiro , he developed the Shapiro–Wilk test , which can indicate whether a sample of numbers would be unusual if it came from a Gaussian distribution .
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Kolmogorov–Smirnov test; Cramér–von Mises criterion; Anderson–Darling test; Berk-Jones tests [1] [2] Shapiro–Wilk test; Chi-squared test; Akaike information criterion; Hosmer–Lemeshow test; Kuiper's test; Kernelized Stein discrepancy [3] [4] Zhang's Z K, Z C and Z A tests [5] Moran test; Density Based Empirical Likelihood Ratio tests [6]
As inflation continued to rear its ugly head, consumers slashed their discretionary spending, tilting some companies to file for bankruptcy. Other brands fell victim to changing trends or even ...