Product-Moment and Partial Correlations

Select Correlation matrices on the Basic Statistics and Tables - Quick tab and click OK to display the Product-Moment and Partial Correlations dialog box, which contains four tabs: Quick, Advanced, Options, and Color Maps. The options on these tabs are used to create correlation matrices for the selected variables. A general discussion of correlation matrices is provided in the Overview. For other correlation or distance measures, use Nonparametric or Cluster Analysis. You can also use Multiple Regression to compute multiple correlations. See Matrix file format for further details.

One variable list. Click this button to display a standard single variable list selection dialog box. Use this option to compute a square matrix of correlations. Note that such matrices can be saved (via the Matrix button, see Advanced tab) for further analysis with other modules (e.g., Multiple Regression, Factor Analysis, Multidimensional Scaling, etc).

Two lists (rect. matrix). Click this button to display a standard two-variable list selection dialog box. Use this option to compute a rectangular matrix of correlations for two lists. Note that rectangular correlation matrices cannot be saved for further analysis with other modules; however, partial correlations can be saved.

Summary. Click this button to produce a spreadsheet containing the correlation matrix for the currently selected variables. The computation of correlations and the display format depends on the current settings on the Options tab.

Cancel. Click this button to close the dialog box without performing an analysis and return to the Basic Statistics and Tables dialog box.

Options. Click this button to display the Options menu.

By Group.  Click this button to display the By Group specification dialog box.

S. Click this button to display the Analysis/Graph Case Selection Conditions dialog box, which contains options to create conditions for which cases will be included (or excluded) in the current analysis. More information is available in the case selection conditions overview and syntax summary.

W. Click the W (weight) button to display the Analysis/Graph Case Weights dialog box, which contains options to adjust the contribution of individual cases to the outcome of the current analysis by "weighting" those cases in proportion to the values of a selected variable.

Weighted moments. Select this check box to specify that each observation contributes the weighting variable's value for that observation. The weight values need not be integers. This module can use fractional case weights in most computations. Some other modules use case weights as integer case multipliers or frequency values. This option is available only after you have defined a weight variable via the W option described above.

DF = W-1 / N-1. When the Weighted moments check box is selected, statistics related to the moments (e.g., standard deviations and variances, skewness, kurtosis) can be based on the sum of the weight values for the weighting variable (W-1), or on the number of (unweighted) observations (N-1). The sums (and means), and sums of squares and cross products are always based on the weighted values of the respective observations. However, in computations requiring the degrees of freedom (e.g., standard deviation, t-test, etc.), the value for the degrees of freedom can either be computed as the sum of the weight values minus one, or as the number of observations minus one. Moment statistics (except for the mean) are based on the sum of the weight values for the weighting variable when the W-1 option button is selected, and are based on the number of (unweighted) observations when the N-1 option button is selected. When the Weighted moments check box is selected, several graphics options are not available. For more information on options for using integer case weights, see also Selecting a weighting variable.

MD deletion. When Casewise deletion of missing data is selected, Statistica ignores all cases that have missing data for any of the variables selected in the list. When Pairwise deletion of missing data is selected, all valid data points are included in the analyses for the respective variables (resulting possibly in unequal valid N per variable).