A Step-by-Step Guide to Selecting the Right Statistical Test - Choose Between Tests for Differences or Associations

When selecting a statistical test, first determine whether you want to test for differences between groups or associations between variables. Tests for differences compare means or proportions between two or more groups. For example, a t-test compares the mean difference between two groups, while an ANOVA tests for differences between the means of three or more groups. Chi-square tests compare categorical data and test for differences in proportions between groups.

Tests for associations quantify the strength of relationships between variables. Simple linear regression assesses the relationship between one independent and one dependent variable. Multiple regression allows several independent variables to predict one outcome. Correlation coefficients like Pearson's r measure the strength of linear relationships between continuous variables. Other coefficients like Spearman's rho and Kendall's tau apply to monotonic relationships.