Setting Options

Option Name	Description
Methods
Missing values	specifies how to treat observations with missing values. If you select the Use nonmissing values for all selected variables option, all observations with missing values are excluded from the analysis. If you select the Use nonmissing values for pairs of variables option, the correlation statistics are computed using the nonmissing pairs of variables.
Statistics
By default, the results contain a table with the correlations and p-values. You can also include these statistics: Correlations Selecting this option includes the correlations in the results. You can also specify probabilities that are associated with each correlation coefficient and whether to order the correlations from highest to lowest in absolute value. Covariances Selecting this option includes the variance and covariance matrix in the results. Also, the Pearson correlations are displayed. If you assign a column to the Partial variables role, the task computes a partial covariance matrix. Sum of squares and cross-products Selecting this option displays a table of the sums of squares and cross products in the results. The Pearson correlations are also included in the results. If you assign a column to the Partial variables role, the unpartial sums of squares and cross-products matrix is displayed. Corrected sum of squares and cross-products Selecting this option displays a table of the corrected sums of squares and cross products. The Pearson correlations are also included in the results. If you assign a column to the Partial variables role, the task computes both an unpartial and a partial corrected sum of squares and cross-products matrix. Descriptive statistics Selecting this option includes the simple descriptive statistics for each variable. Even if you do not select this option and you choose to create an output data set, the data set contains the descriptive statistics for the variables.
Fisher’s z transformation For a Pearson correlation, you can use the Fisher transformation options to request confidence limits and p-values under a specified alternative (null) hypothesis, , for correlation coefficients that use Fisher’s z transformation. If you select the Fisher’s z transformation check box, you must specify a value in the Null hypothesis box. You can choose from these types of confidence limits: Two-sided confidence limits requests two-sided confidence limits for the test of the null hypothesis, . This is the default. Lower confidence limit requests a lower confidence limit for the test of the one-sided null hypothesis, . Upper confidence limit requests an upper confidence limit for the test of the one-sided null hypothesis, . By default, the level of the confidence limits for the correlation is 95%.
Nonparametric Correlations
Spearman’s rank-order correlation	calculates Spearman rank-order correlation. This is a nonparametric measure of association that is based on the rank of the data values. The correlations range from –1 to 1.
Kendall’s tau-b	calculates Kendall tau-b. This is a nonparametric measure of association that is based on the number of concordances and discordances in paired observations. Concordance occurs when paired observations vary together, and discordance occurs when paired observations vary differently. Kendall's tau-b ranges from –1 to 1.
Hoeffding’s measure of dependence	calculates Hoeffding's measure of dependence, D. This is a nonparametric measure of association that detects more general departures from independence. This D statistic is 30 times larger than the usual definition and scales the range between –0.5 and 1 so that only large positive values indicate dependence.
Plots
You can include either of these plots in your results: a scatter plot matrix for variables. You can also choose to include a histogram of the analysis variables in the symmetric matrix plot. a scatter plot for each applicable pair of distinct variables from the analysis variables. You can specify whether to display the prediction ellipses for new observations or the confidence ellipses for the mean. You can also specify the number of variables to plot and the maximum number of points to plot.