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  2. Tukey's test of additivity - Wikipedia

    en.wikipedia.org/wiki/Tukey's_test_of_additivity

    The most common setting for Tukey's test of additivity is a two-way factorial analysis of variance (ANOVA) with one observation per cell. The response variable Y ij is observed in a table of cells with the rows indexed by i = 1,..., m and the columns indexed by j = 1,..., n. The rows and columns typically correspond to various types and levels ...

  3. Two-way analysis of variance - Wikipedia

    en.wikipedia.org/wiki/Two-way_analysis_of_variance

    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 variables on one continuous dependent variable. The two-way ANOVA not only aims at assessing the main effect of each independent variable but also if there is any interaction between them.

  4. Analysis of variance - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_variance

    The underlying principle of ANOVA is based on the law of total variance, which states that the total variance in a dataset can be broken down into components attributable to different sources. In the case of ANOVA, these sources are the variation between groups and the variation within groups. ANOVA was developed by the statistician Ronald Fisher.

  5. Multivariate analysis of variance - Wikipedia

    en.wikipedia.org/wiki/Multivariate_analysis_of...

    The image above depicts a visual comparison between multivariate analysis of variance (MANOVA) and univariate analysis of variance (ANOVA). In MANOVA, researchers are examining the group differences of a singular independent variable across multiple outcome variables, whereas in an ANOVA, researchers are examining the group differences of sometimes multiple independent variables on a singular ...

  6. Interaction (statistics) - Wikipedia

    en.wikipedia.org/wiki/Interaction_(statistics)

    From the graph and the data, it is clear that the lines are not parallel, indicating that there is an interaction. This can be tested using analysis of variance (ANOVA). The first ANOVA model will not include the interaction term. That is, the first ANOVA model ignores possible interaction. The second ANOVA model will include the interaction term.

  7. Blocking (statistics) - Wikipedia

    en.wikipedia.org/wiki/Blocking_(statistics)

    Without blocking: diet pills vs placebo on weight loss. In our previous diet pills example, a blocking factor could be the sex of a patient. We could put individuals into one of two blocks (male or female). And within each of the two blocks, we can randomly assign the patients to either the diet pill (treatment) or placebo pill (control).

  8. ANOVA–simultaneous component analysis - Wikipedia

    en.wikipedia.org/wiki/ANOVA–simultaneous...

    It combines the principles of two other methods: Analysis of Variance (ANOVA), which assesses how much of the variation in a dataset is explained by different experimental conditions or factors, and Simultaneous Component Analysis (SCA), mathematically equivalent to Principal Component Analysis (PCA), which simplifies the interpretation of ...

  9. Kruskal–Wallis test - Wikipedia

    en.wikipedia.org/wiki/Kruskal–Wallis_test

    The Kruskal–Wallis test by ranks, Kruskal–Wallis test (named after William Kruskal and W. Allen Wallis), or one-way ANOVA on ranks is a non-parametric statistical test for testing whether samples originate from the same distribution. [1] [2] [3] It is used for comparing two or more independent samples of equal or different sample sizes.