This example does not examine the correlation matrix but assumes that all items are positively correlated. Normally, you want to examine the correlation and covariance matrices to make sure that all variables are positively correlated.
Positive correlation is needed because items measure a common entity.
You exclude negatively correlated items from the analysis because they do not measure the same construct. These calculations use the 23 observations without missing values. Because the variances of some variables vary widely, you use the standardized scores to estimate reliability. The overall standardized alpha of .85 is an acceptable reliability coefficient. This is greater than Nunnally's suggested value of .70.