Dependent (outcome) variable: Continuous/numerical/scale (some disciplines also test ordinal data)
Independent (predictor/explanatory) variable: One categorical variable with two groups (binary)
Note: Some people use parametric tests for ordinal data if there are quite a few ordered categories. A significant result means the groups are different but interpreting the mean difference can be tricky.Use: Used to detect the difference in the means of two different groups of subjects (independent groups).
Assumptions: The dependent variable should be approximately normally distributed within each group. If a histogram or QQplot suggests the data are vey skewed or the dependent variable is ordinal, a Mann-Whitney or Wilcoxon rank sum test (which are based on ranks rather than the raw data) can be used instead of the t-test.
Data notes Ensure there is only one row per participant with the outcome variable in one column and another column containing the group.
Click on the download button to get the appropriate resource for the test and software package you want help with.
|SPSS||R Sheet||R Script||Jamovi||SAS||
|Independent t-test||Mann-Whitney/ Wilcoxon Rank Sum (Non-parametric independent t-test)|