ABSTRACT
Some degree of correlation exists in almost all datasets. Different types of correlation exist and understanding the differences allows for greater understanding and use of statistical tests. This chapter outlines the purpose and history of correlation in planning practice. It also provides a background into the mechanics of correlation by showing how to calculate correlation coefficients; defining and explaining positive and negative correlations; and providing examples of Pearson’s, Spearman’s, and Intraclass Correlation Coefficients. The chapter then provides a step-by-step guide for running SPSS and R tests of correlation and how to read the results. The chapter concludes with two planning examples of correlation in published research articles.
