The CORR Procedure
- Overview
- Getting Started
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Syntax
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Details
Pearson Product-Moment Correlation Spearman Rank-Order Correlation Kendall’s Tau-b Correlation Coefficient Hoeffding Dependence Coefficient Partial Correlation Fisher’s z Transformation Polyserial Correlation Cronbach’s Coefficient Alpha Confidence and Prediction Ellipses Missing Values In-Database Computation Output Tables Output Data Sets ODS Table Names ODS Graphics
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Examples
Computing Four Measures of Association Computing Correlations between Two Sets of Variables Analysis Using Fisher’s z Transformation Applications of Fisher’s z Transformation Computing Polyserial Correlations Computing Cronbach’s Coefficient Alpha Saving Correlations in an Output Data Set Creating Scatter Plots Computing Partial Correlations
- References
| Spearman Rank-Order Correlation |
Spearman rank-order correlation is a nonparametric measure of association based on the ranks of the data values. The formula is
 |
where 
is the rank of 
, 
is the rank of 
, 
is the mean of the values, and 
is the mean of the values.
PROC CORR computes the Spearman correlation by ranking the data and using the ranks in the Pearson product-moment correlation formula. In case of ties, the averaged ranks are used.
degrees of freedom, where 
is the sample Spearman correlation.