In this chapter presents exact and Monte Carlo permutation statistical methods for measures of linear correlation and association. Also presented in this chapter is a permutation-based measure of effect size for a variety of measures of correlation and association. Simple linear correlation between two variables constitutes the foundation for a large family of advanced analytic techniques and is taught in every introductory course on statistical methods. In addition, this chapter presents a number of non-parametric measures of correlation and association with permutation-based alternatives, including Spearman’s rank-order correlation coefficient, Kendall’s \(\tau _{a}\) and \(\tau _{b}\) measures of ordinal association, and Spearman’s footrule measure of disarray.