Search results
Results from the WOW.Com Content Network
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 ).
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.
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; 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]
Process: Implementation of Hayes' popular SPSS PROCESS module for JASP; Prophet: A simple model for time series prediction. Quality Control: Investigate if a manufactured product adheres to a defined set of quality criteria. Reliability: Quantify the reliability of test scores. Robust T-Tests: Robustly evaluate the difference between two means.
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 .
“For example, ‘I hope your test went well. I know you studied hard for that,’ or ‘What a beautiful day today. I hope you had fun at recess.’” ...
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 .