Enter your Partial Correlation Coefficient (β) in the Box Below
Select Which Type of Design Best Describes your Analysis
T-Tests
Compare the mean value of two independent groups on a single continuous outcome variable.
Mann-Whitney Test
Non-parametric version of the t-test. Compare the average rank of two independent groups on a single ordinal outcome variable.
One-Way ANOVA
Compare the mean value of three to five independent groups on a single continuous outcome variable.
MANOVA
Compare the mean of two groups on multiple continuous outcome variables.
Linear
Correlation
Examine the linear association between two continuous outcome variables.
Monotonic
Corrrelation
Non-parametric version of the linear correlation. Examine the monotonic association between two ordinal outcome variables.
Linear Regression (Main Effect Only)
Examine the linear association between a focal predictor on a continuous outcome, controlling for the level of other variables.
Linear Regression (Main Effect with Interaction)
Examine the linear association between a focal predictor on a continuous outcome at a specific level of a moderating variable, controlling for the level of other variables.
2 x 2 Contingency Table
Examine the linear association between two dichotomous variables.
Logistic Regression
Examine the association between a focal dichotomous treatment on a binary outcome variable measuring a negative outcome, controlling for other variables.