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Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data

Author

Listed:
  • Hauke Jan

    (Institute of Socio-Economic Geography and Spatial Management, Adam Mickiewicz University, Poznań, Poland)

  • Kossowski Tomasz

    (Institute of Socio-Economic Geography and Spatial Management, Adam Mickiewicz University, Poznań, Poland)

Abstract

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 product-moment 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.

Suggested Citation

  • Hauke Jan & Kossowski Tomasz, 2011. "Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data," Quaestiones Geographicae, Sciendo, vol. 30(2), pages 87-93, June.
    • Handle: RePEc:vrs:quageo:v:30:y:2011:i:2:p:87-93:n:9
    DOI: 10.2478/v10117-011-0021-1
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