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

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

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...

Variance-based sensitivity analysis (often referred to as the Sobol’ method or Sobol’ indices, after Ilya M. Sobol’) is a form of global sensitivity analysis...

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...

Analysis of molecular variance (AMOVA), is a statistical model for the molecular algorithm in a single species, typically biological. The name and model...

decomposes the variance in the DV into variance explained by the CV(s), variance explained by the categorical IV, and residual variance. Intuitively, ANCOVA...

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...

In statistics, a mixed-design analysis of variance model, also known as a split-plot ANOVA, is used to test for differences between two or more independent...

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

The law of total variance is a fundamental result in probability theory that expresses the variance of a random variable Y in terms of its conditional...

determined). The term is most often used in the context of linear models (linear regression, analysis of variance), where certain random vectors are constrained...

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

the multivariate analysis of variance and covariance analyses (MANOVA, ANOVA, ANCOVA). In addition to being thought of as a form of multiple regression...

align with the true directions of maximal variance. Mean-centering is unnecessary if performing a principal components analysis on a correlation matrix, as...

In statistics, analysis of rhythmic variance (ANORVA) is a method for detecting rhythms in biological time series, published by Peter Celec (Biol Res...

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

associated box plot. Entries in an analysis of variance table can also be regarded as summary statistics.: 378  Common measures of location, or central tendency...

Analysis of categorical data Analysis of covariance Analysis of molecular variance Analysis of rhythmic variance Analysis of variance Analytic and enumerative...

econometrics and other applications of multivariate time series analysis, a variance decomposition or forecast error variance decomposition (FEVD) is used to...

form of response-surface equations. Many different models are used in MVA, each with its own type of analysis: Multivariate analysis of variance (MANOVA)...

In statistics, pooled variance (also known as combined variance, composite variance, or overall variance, and written σ 2 {\displaystyle \sigma ^{2}} )...

the point of view of exploratory analysis, the eigenvalues of PCA are inflated component loadings, i.e., contaminated with error variance. Whilst EFA...

plot Shapiro–Francia test Shapiro, S. S.; Wilk, M. B. (1965). "An analysis of variance test for normality (complete samples)". Biometrika. 52 (3–4): 591–611...

data analysis or to allow the application of simple regression-based or analysis of variance techniques. The aim behind the choice of a variance-stabilizing...

interactions of several factors (independent variables). Analysis of experiment design is built on the foundation of the analysis of variance, a collection of models...

related to analysis of variance (ANOVA) and regression analysis, which also attempt to express one dependent variable as a linear combination of other features...

errors have a mean of zero, are uncorrelated, normally distributed, and have equal variances, the best linear unbiased estimator of the coefficients is...

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