used by people in more than 230 countries!

Below you will find descriptions and links to 14 free statistics calculators for computing values associated with regression studies.

If you like, you may also use the search page to help you find what you need.

This calculator will tell you the minimum required sample size for a multiple regression study, given the desired probability level, the number of predictors in the model, the anticipated effect size, and the desired statistical power level.

This calculator will compute an adjusted R^{2} value (i.e., the population squared multiple correlation), given an observed (sample) R^{2}, the number of predictors in the model, and the total sample size.

This calculator will tell you the beta level for your study (i.e., the Type II error rate), given the observed probability level, the number of predictors, the observed R^{2}, and the sample size.

This calculator will compute the 99%, 95%, and 90% confidence intervals for a predicted value of a regression equation, given a predicted value of the dependent variable, the standard error of the estimate, the number of predictors in the model, and the total sample size.

This calculator will tell you the critical value of the F-distribution, given the probability level, the numerator degrees of freedom, and the denominator degrees of freedom.

This calculator will tell you the effect size for a multiple regression study (i.e., Cohen's f^{2}), given a value of R^{2}.

This calculator will compute the 99%, 95%, and 90% confidence intervals for the f^{2} effect size associated with a multiple regression study, given the f^{2} value, the number of predictors in the model, and the total sample size.

This calculator will tell you the Fisher F-value for a multiple regression study and its associated probability level (p-value), given the model R^{2}, the number of predictors in the model, and the total sample size.

This calculator will tell you the observed power for your multiple regression study, given the observed probability level, the number of predictors, the observed R^{2}, and the sample size.

This calculator will compute an R^{2} value for a multiple regression model, given Cohen's f^{2} effect size for the model.

This calculator will compute the 99%, 95%, and 90% confidence intervals for an R^{2} value (i.e., a squared multiple correlation), given the value of the R-square, the number of predictors in the model, and the total sample size.

This calculator will compute the 99%, 95%, and 90% confidence intervals for a regression coefficient, given the value of the regression coefficient, the standard error of the regression coefficient, the number of predictors in the model, and the total sample size.

This calculator will compute the 99%, 95%, and 90% confidence intervals for a regression intercept (i.e., the regression constant), given the value of the regression intercept, the standard error of the regression intercept, the number of predictors in the model, and the total sample size.

This calculator will determine whether the slopes of two lines are significantly different from each other, given the slope, standard error, and sample size for each line. Values returned from the calculator include the probability value, the t-value for the significance test, and the degrees of freedom. A probability value of less than 0.05 indicates that the two slopes are significantly different from each other.