This page contains brief descriptions of statistical tests to help analysts determine what types analyses may be applicable to their study. This page not meant to be a complete guide on the appropriateness of any given test, but rather general guidelines to the types of variables that can be used with each type of statistical analysis. Analyses are in alphabetical order.
- If you would prefer to see all available analysis listed alphabetically, please click here: Analyses in Alphabetical Order
- If you would prefer to see all available analysis broken down by topic, please click here: List of Analyses by Topic
Brief Methods
| Analysis | Dependent / Response Variable | Independent Variables(s) | Notes & Assumptions |
|---|---|---|---|
| Two Independent Samples t-test | Continuous | Categorical (with >2 levels) | The response variable is not normally distributed, and/or you have signficant outliers. Analogous to a nonparametric one-way ANOVA |
| Mann-Whitney U test | Continuous | Categorical (with 2 levels) | The response variable is not normally distributed, and/or you have signficant outliers. Analogous to a nonparametric independent sample t-test |
| Mann-Whitney U test | Continuous | Categorical (with >2 levels) | The response variable should be normally distributed, minimal outliers, equal variances |
| Paired t-test | Continuous | Categorical (with >2 levels) | The difference between groups (matched pairs) should be normally distributed, minimal outliers |
| Paired t-test | Continuous | Categorical (with 2 levels) | The response variable should be normally distributed, minimal outliers |
| Wilcoxon signed-rank test | Continuous | Categorical (with 2 levels) | The difference between groups (matched pairs) are not normally distributed, and/or you have signficant outliers. Analogous to a nonparametric paired samples t-test |
