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...

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...

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

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...

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

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...

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

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

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

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

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

crosses. The method makes use of a genetic map of the typed markers, and, like analysis of variance, assumes the presence of a single QTL. In interval mapping...

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

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...

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

results relating to the probability distributions of statistics that are used in the analysis of variance. If X1, ..., Xn are independent normally distributed...

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...

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

introductory text for analysis of variance (one-way, multi-way, factorial, split-plot, and unbalanced designs). Also analysis of co-variance, multiple and partial...

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

minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has lower variance than...

statistics, an F-test of equality of variances is a test for the null hypothesis that two normal populations have the same variance. Notionally, any F-test...

model, also called a variance components model, is a statistical model where the model parameters are random variables. It is a kind of hierarchical linear...

Polynomial least squares describes the variance in a prediction of the dependent variable as a function of the independent variable and the deviations...

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...