Brief Descriptions of Statistical Methods

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.

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
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