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dc.contributor.authorHauke, Jan-
dc.contributor.authorKossowski, Tomasz-
dc.identifier.citationQuaestiones Geographicae vol. 30 (2), 2011, pp. 87-93pl_PL
dc.description.abstractSpearman’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.pl_PL
dc.publisherWydział Nauk Geograficznych i Geologicznych Uniwersytetu im. Adama Mickiewiczapl_PL
dc.subjectPearson’s correlation coefficientpl_PL
dc.subjectSpearman’s rank correlation coefficientpl_PL
dc.subjectKendall’s taupl_PL
dc.subjectregional indices of socio-economic developmentpl_PL
dc.titleComparison of values of Pearson’s and Spearman’s correlation coefficient on the same sets of datapl_PL
Appears in Collections:Quaestiones Geographicae vol. 30 (2), 2011

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