Below you will find complete descriptions and links to 5 different analytics calculators for computing analytics-related effect sizes.

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Compute the 90%, 95%, and 99% confidence intervals for Cohen's f-square effect size for a multiple regression study, given the f-square value, the number of predictor variables, and the total sample size. Knowing the confidence interval for an f-square effect size can be very useful for comparing different models in analytics studies that rely on multiple regression.

Compute Cohen's f-square effect size for a hierarchical multiple regression study, given an R-square value for a set of predictor variables A, and an R-square value for the sum of A and another set of predictor variables B. The calculator computes the effect size attributable to the addition of set B, which can provide useful insights for analytics studies that rely on hierarchical regression.

Compute Cohen's f-square effect size for a multiple regression study, given the study's R-square value. Effect sizes are often useful in analytics for quantifying the substantive value of the statistical model.

Compute an R-square value for a multiple regression model, given the value of Cohen's f-square effect size for the model. Knowing the R-square value for a regression model is often very useful for assessing and comparing different regression models in analytics studies.

Compute the two-tailed Cohen's d effect size for a t-test, given the mean and standard deviation for two independent samples of equal size. Knowing the effect size is often very useful when comparing or reporting the results of analytics studies that rely on t-tests.