Table of Contents
8 relations: Bartlett's test, Covariance matrix, George E. P. Box, Homogeneity and heterogeneity, Levene's test, Linear discriminant analysis, Multivariate analysis of variance, Multivariate normal distribution.
Bartlett's test
In statistics, Bartlett's test, named after Maurice Stevenson Bartlett, is used to test homoscedasticity, that is, if multiple samples are from populations with equal variances. Box's M test and Bartlett's test are Statistical tests.
See Box's M test and Bartlett's test
Covariance matrix
In probability theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between each pair of elements of a given random vector.
See Box's M test and Covariance matrix
George E. P. Box
George Edward Pelham Box (18 October 1919 – 28 March 2013) was a British statistician, who worked in the areas of quality control, time-series analysis, design of experiments, and Bayesian inference.
See Box's M test and George E. P. Box
Homogeneity and heterogeneity
Homogeneity and heterogeneity are concepts relating to the uniformity of a substance, process or image.
See Box's M test and Homogeneity and heterogeneity
Levene's test
In statistics, Levene's test is an inferential statistic used to assess the equality of variances for a variable calculated for two or more groups. Box's M test and Levene's test are Statistical tests.
See Box's M test and Levene's test
Linear discriminant analysis
Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or events.
See Box's M test and Linear discriminant analysis
Multivariate analysis of variance
In statistics, multivariate analysis of variance (MANOVA) is a procedure for comparing multivariate sample means.
See Box's M test and Multivariate analysis of variance
Multivariate normal distribution
In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions.
See Box's M test and Multivariate normal distribution