How can correlation be more effectively used so that one does not misinterpret the data? This book reveals how to do this by examining Pearsonrfrom its conceptual meaning, to assumptions, special cases of the Pearsonr, the biserial coefficient and tetrachoric coefficient estimates of the Pearsonr, its uses in research (including effect size, power analysis, meta-analysis, utility analysis, reliability estimates and validation), factors that affect the Pearsonr, and finally to additional nonparametric correlation indexes. After reading this book, the reader will be able to compare and distinguish the concepts of similarity and relationship, identify the distinction between correlation and causation and to interpret correlations correctly.