Spearman's Rank Correlation Coefficient is a measure of association between the rankings of two variables measured on N individuals (i.e. two vectors of length N). The correlation coefficient is calculated from the vectors of ranks for each pair of samples.
Kendall's rank correlation coefficient, tau, is a measure of association between the rankings of two variables measured on N individuals. It is calculated as S / SQRT(NC1 * NC2). S is defined as the sum of SIGN(Xi - Xj) * SIGN(Yi - Yj)) over all pair of distinct units i and j. NC1 and NC2 are the number of valid comparisons (removing ties and missing values) that can be made amongst the first and second set of samples, respectively.
| List of Variates | The samples must be supplied as a list of variates, whose names should be entered in the List of Data box |
| One Variate with Groups | The data must be supplied in one variate, specified as the Data Set. Membership of the different samples is then indicated by the Groups factor |
| Test | Correlation coefficient/matrix and relevant test statistics (Spearman rank correlation only). |
| Probabilities | Probability for correlation coefficient (Kendall's tau only). |
| Correlations | Rank correlation coefficient. |
| Ranks | Ranks for each sample. |