This chapter introduces conventional and permutation methods for two-sample tests. The chapter contains example analyses illustrating computation of exact permutation probability values for two-sample tests, calculation of measures of effect size for two-sample tests, exact and Monte Carlo permutation procedures for two-sample tests, and the application of permutation methods to two-sample rank-score data. Also included in the chapter are permutation versions of Student’s two-sample t test, the Wilcoxon–Mann–Whitney two-sample rank-sum test, and a permutation-based alternative for the four conventional measures of effect size for two-sample tests: Cohen’s \(\hat{d}\) , Pearson’s \(r^{2}\) , Kelley’s \(\epsilon ^{2}\) , and Hays’ \(\hat{\omega }^{2}\) .