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  2. Analysis of variance - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_variance

    The definitional equation of sample variance is = (¯), where the divisor is called the degrees of freedom (DF), the summation is called the sum of squares (SS), the result is called the mean square (MS) and the squared terms are deviations from the sample mean. ANOVA estimates 3 sample variances: a total variance based on all the observation ...

  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. 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".

  5. Mixed-design analysis of variance - Wikipedia

    en.wikipedia.org/wiki/Mixed-design_analysis_of...

    Andy Field (2009) [1] provided an example of a mixed-design ANOVA in which he wants to investigate whether personality or attractiveness is the most important quality for individuals seeking a partner. In his example, there is a speed dating event set up in which there are two sets of what he terms "stooge dates": a set of males and a set of ...

  6. JASP - Wikipedia

    en.wikipedia.org/wiki/JASP

    Descriptives: Explore the data with tables and plots. T-Tests: Evaluate the difference between two means. ANOVA: Evaluate the difference between multiple means. Mixed Models: Evaluate the difference between multiple means with random effects. Regression: Evaluate the association between variables. Frequencies: Analyses for count data.

  7. Mauchly's sphericity test - Wikipedia

    en.wikipedia.org/wiki/Mauchly's_sphericity_test

    Developed in 1940 by John W. Mauchly, [3] Mauchly's test of sphericity is a popular test to evaluate whether the sphericity assumption has been violated. The null hypothesis of sphericity and alternative hypothesis of non-sphericity in the above example can be mathematically written in terms of difference scores.

  8. F-test - Wikipedia

    en.wikipedia.org/wiki/F-test

    Common examples of the use of F-tests include the study of the following cases . One-way ANOVA table with 3 random groups that each has 30 observations. F value is being calculated in the second to last column The hypothesis that the means of a given set of normally distributed populations, all having the same standard deviation, are equal.

  9. 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.