In statistics, multivariate analysis of variance (MANOVA) is a procedure for comparing multivariate sample means. As a multivariate procedure, it is used...

Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e.,...

multivariate analysis of variance (PERMANOVA), is a non-parametric multivariate statistical permutation test. PERMANOVA is used to compare groups of objects...

regression analysis, factor analysis, canonical correlation analysis, discriminant analysis, as well as more general families of models in the multivariate analysis...

Multivariate analysis of covariance (MANCOVA) is an extension of analysis of covariance (ANCOVA) methods to cover cases where there is more than one dependent...

Analysis of variance (ANOVA) is a family of statistical methods used to compare the means of two or more groups by analyzing variance. Specifically, ANOVA...

In statistics, one-way analysis of variance (or one-way ANOVA) is a technique to compare whether two or more samples' means are significantly different...

In statistics, the two-way analysis of variance (ANOVA) is an extension of the one-way ANOVA that examines the influence of two different categorical independent...

variance in the dependent variable might actually reduce power. MANCOVA (Multivariate analysis of covariance) Keppel, G. (1991). Design and analysis:...

"within-samples" sum of squares and "between-samples" sum of squares, i.e., partitioning of the sum of squares. In multivariate analysis of variance (MANOVA) the...

distribution used in multivariate hypothesis testing, especially with regard to the likelihood-ratio test and multivariate analysis of variance (MANOVA). Wilks'...

in statistics is a specific multivariate linear model, also known as GMANOVA (Generalized Multivariate Analysis-Of-Variance). It generalizes MANOVA by...

scalar. Discriminant analysis of principal components (DAPC) is a multivariate method used to identify and describe clusters of genetically related individuals...

heteroscedasticity is a major concern in regression analysis and the analysis of variance, as it invalidates statistical tests of significance that assume that the modelling...

on multivariate medians (specifically, the spatial median). This optimization-based definition of the median is useful in statistical data-analysis, for...

areal unit problem Multivariate adaptive regression spline Multivariate normal distribution Pearson correlation coefficient Quasi-variance Prediction interval...

Wichern (2002, p. 312, “Multivariate two-way fixed-effects model with interaction”, in “6.6 Two-way multivariate analysis of variance”, p. 307–317) Mardia...

In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation...

splines Multivariate analysis Multivariate analysis of variance Multivariate distribution – see Joint probability distribution Multivariate kernel density...

combined effect size across all of the studies. As such, this statistical approach involves extracting effect sizes and variance measures from various studies...

analysis (LSSA) is a method of estimating a frequency spectrum based on a least-squares fit of sinusoids to data samples, similar to Fourier analysis...

statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional...

parametric equivalent of the Kruskal–Wallis test is the one-way analysis of variance (ANOVA). A significant Kruskal–Wallis test indicates that at least...

probability distribution of all of these variables, which is the domain of multivariate analysis. Linear regression is also a type of machine learning algorithm...

"Factor Analysis," from Statnotes: Topics in Multivariate Analysis. Retrieved on April 13, 2009, from StatNotes: Topics in Multivariate Analysis, from G...

multivariate analysis of variance (MANOVA analysis) to compare group means on a combination of dependent variables. In the spectral decomposition of matrices...

modelling involving the multivariate generalisation of sums of squares, see Multivariate analysis of variance For the sum of squares of consecutive integers...

the analysis of variance (ANOVA). F test of analysis of variance (ANOVA) follows three assumptions Normality (statistics) Homogeneity of variance Independence...

Bayesian analysis for outlier problems, variance components, linear models and multivariate statistics. Theory of Probability Author: Bruno de Finetti Publication...

dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between each pair of elements of a given random...