Variance analysis - ορισμός. Τι είναι το Variance analysis
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Τι (ποιος) είναι Variance analysis - ορισμός

COLLECTION OF STATISTICAL MODELS USED TO ANALYZE THE DIFFERENCES BETWEEN GROUP MEANS AND THEIR ASSOCIATED PROCEDURES
ANOVA; Analysis of Variance; Analysis of variance/Random effects models; Analysis of variance/Degrees of freedom; Annova; Anova; Factorial ANOVA; Multi-factor analysis of variance; Variance analysis; ANOVAR; ANOVA/Random; ANOVA/DegreesOfFreedom; Analysis of variance/Fixed effects model; ANOVA/Fixed; AN.O.VA.
  • Fair fit: Pet vs Working breed and less athletic vs more athletic
  • Very good fit: Weight by breed
  • No fit: Young vs old, and short-haired vs long-haired

Analysis of variance         
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher.
Analysis of molecular variance         
AMOVA; Analysis of Molecular Variance
Analysis of molecular variance (AMOVA), is a statistical model for the molecular algorithm in a single species, typically biological. The name and model are inspired by ANOVA.
Permutational analysis of variance         
Permutational Analysis of Variance; PERMANOVA
Permutational multivariate analysis of variance (PERMANOVA), is a non-parametric multivariate statistical permutation test. PERMANOVA is used to compare groups of objects and test the null hypothesis that the centroids and dispersion of the groups as defined by measure space are equivalent for all groups.

Βικιπαίδεια

Analysis of variance

Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means. In other words, the ANOVA is used to test the difference between two or more means.