Measures of Association

This chapter starts with a discussion on the historical development of correlation coefficients. It then discusses the population and sample correlations, and compares regression with correlation. A brief discussion on the data assumptions and interpretations of correlation coefficient follows it. The single-variable correlation that has applications in crystallography, medical sciences and many other fields appears in Sect. 1.5.1. Scatterplots and Weibull plots are described next. This is followed by a discussion on correlation vs causation, and other popular types of correlation like phi-coefficient, Gini coefficient, multiple correlation, weighted correlation, rank correlation, angular correlation, piece-wise linear correlation, Matthews correlation, tetrachoric, serial, polyserial, intraclass, and distance correlations. Other topics discussed include Baak et al. (2020) mixed correlation, Chatterjee’s rank correlation (2021), ecological correlation, robust correlation, Lin’s concordance correlation and correlational research.