COMPARISON OF VALUES OF PEARSON’S AND SPEARMAN’S CORRELATION COEFFICIENTS ON THE SAME SETS OF DATA jan hauke, tomasz kossowski

Spearman’s rank correlation coefficient is a nonparametric (distribution-free) rank statistic proposed by Charles Spearman as a measure of the strength of an association between two variables. It is a measure of a monotone association that is used when the distribution of data makes Pearson’s correlation coefficient undesirable or misleading. Spearman’s coefficient is not a measure of the linear relationship between two variables, as some “statisticians” declare. It assesses how well an arbitrary monotonic function can describe a relationship between two variables, without making any assumptions about the frequency distribution of the variables. Unlike Pearson’s product-moment correlation coefficient, it does not require the assumption that the relationship between the variables is linear, nor does it require the variables to be measured on interval scales; it can be used for variables measured at the ordinal level. The idea of the paper is to compare the values of Pearson’s productmoment correlation coefficient and Spearman’s rank correlation coefficient as well as their statistical significance for different sets of data (original for Pearson’s coefficient, and ranked data for Spearman’s coefficient) describing regional indices of socio-economic development. key words: Pearson’s correlation coefficient, Spearman’s rank correlation coefficient, Kendall’s tau, regional indices of socio-economic development Jan Hauke, Tomasz Kossowski, Institute of Socio-Economic Geography and Spatial Management, Adam Mickiewicz University, ul. Dzięgielowa 27, 61-680 Poznań, Poland; e-mail: [email protected], [email protected]