Difference between revisions of "Calculate Spearman's Rank Correlation Coefficient"
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{{fa}}Spearman's rank correlation coefficient allows you to identify whether two variables relate in a monotonic function (i.e., that when one number increases, so does the other, or vice versa). To calculate Spearman's rank correlation coefficient, you'll need to rank and compare data sets to find Σd<sup>2</sup>, then plug that value into the standard or simplified version of Spearman's rank correlation coefficient formula. You can also calculate this coefficient using Excel formulas or R commands. | {{fa}}Spearman's rank correlation coefficient allows you to identify whether two variables relate in a monotonic function (i.e., that when one number increases, so does the other, or vice versa). To calculate Spearman's rank correlation coefficient, you'll need to rank and compare data sets to find Σd<sup>2</sup>, then plug that value into the standard or simplified version of Spearman's rank correlation coefficient formula. You can also calculate this coefficient using Excel formulas or R commands. | ||
| − | [[Category:Probability and Statistics]] | + | [[Category: Probability and Statistics]] |
== Steps == | == Steps == | ||
=== Calculation Help === | === Calculation Help === | ||
