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  2. 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.

  3. 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 ...

  4. Analysis of variance - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_variance

    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 compares the amount of variation between the group means to the amount of variation within each group. If the between-group variation is substantially larger than the within-group variation ...

  5. Interaction (statistics) - Wikipedia

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

    Interaction effect of education and ideology on concern about sea level rise. In statistics, an interaction may arise when considering the relationship among three or more variables, and describes a situation in which the effect of one causal variable on an outcome depends on the state of a second causal variable (that is, when effects of the two causes are not additive).

  6. F-test - Wikipedia

    en.wikipedia.org/wiki/F-test

    F test of analysis of variance (ANOVA) follows three assumptions Normality (statistics) Homogeneity of variance; Independence of errors and random sampling; The hypothesis that a proposed regression model fits the data well. See Lack-of-fit sum of squares. The hypothesis that a data set in a regression analysis follows the simpler of two ...

  7. Analysis of covariance - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_covariance

    Mathematically, ANCOVA decomposes the variance in the DV into variance explained by the CV(s), variance explained by the categorical IV, and residual variance. Intuitively, ANCOVA can be thought of as 'adjusting' the DV by the group means of the CV(s). [1] The ANCOVA model assumes a linear relationship between the response (DV) and covariate (CV):

  8. Squared deviations from the mean - Wikipedia

    en.wikipedia.org/wiki/Squared_deviations_from...

    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.

  9. One-way analysis of variance - Wikipedia

    en.wikipedia.org/wiki/One-way_analysis_of_variance

    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 (using the F distribution). This analysis of variance technique requires a numeric response variable "Y" and a single explanatory variable "X", hence "one-way".