effect size

effect size

Effect size is a measure of the size of the effect of the explanatory variable on the outcome variable.

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    • Cohen’s d

      Cohen’s d is the measure of effect size; it indicates the size of a group difference in number of standard deviation.

    • cohensD()

      The cohensD() function calculates the Cohen's d measure of effect size. Example: cohensD(Thumb ~ Gender , data = Fingers) Example output:

    • independent sampling

      Independent sampling is the selection of one case for a study has no effect on the selection of another case.

    • gf_lm()

      The gf_lm() function overlays the best-fitting regression line on a scatter plot when chained onto gf_point(). Example: # adds a regression line gf_point(Thumb ~ Height, data = Fingers) %>%       gf_lm( color = "orange", size = 2 )

    • Central Limit Theorem (CLT)

      Central Limit Theorem (CLT) describes the shape, center, and spread of a distribution of sample means of equal size when each sample is randomly chosen from some population.