This article discusses and contrasts the measures of association introduced by Pearson, Spearman, and Kendall, as these are the three most commonly used in practice and also the ones primarily covered in introductory statistics courses. Emphasis is placed on concepts pertaining to the measurement of the level of association between two variables, the calculation of the coefficients, and the interpretation of the calculated values. In particular, we demonstrate how Spearman's rho and Kendall's tau can be expressed in terms of Pearson's correlation coefficient based on transformed data. Important concepts and potential pitfalls are illustrated using numerical examples.