Bivariate Correlations Options
Statistics. For Pearson correlations, you can choose one or both of the following:
- Means and standard deviations. Displayed for each variable. The number of cases with nonmissing values is also shown. Missing values are handled on a variable-by-variable basis regardless of your missing values setting.
- Cross-product deviations and covariances. Displayed for each pair of variables. The cross-product of deviations is equal to the sum of the products of mean-corrected variables. This is the numerator of the Pearson correlation coefficient. The covariance is an unstandardized measure of the relationship between two variables, equal to the cross-product deviation divided by N–1.
Missing Values. You can choose one of the following:
- Exclude cases pairwise. Cases with missing values for one or both of a pair of variables for a correlation coefficient are excluded from the analysis. Since each coefficient is based on all cases that have valid codes on that particular pair of variables, the maximum information available is used in every calculation. This can result in a set of coefficients based on a varying number of cases.
- Exclude cases listwise. Cases with missing values for any variable are excluded from all correlations.
Specifying Options for Bivariate Correlations
- From the
menus choose:
This feature requires the Statistics Base option.
- In the Bivariate Correlations dialog box, click Options.