Discriminant analysis setup - key decisions
You can run discriminant either from the menus or via syntax. When running discriminant analysis, you must make several higher-level decisions about the analysis.
Priors
First, do you have any prior information about the relative sizes of the target variable classes in the population? In the absence of any knowledge of target class sizes, you can use equal prior probabilities, which is the default, or prior probabilities can be in the proportions of the target variable class sizes in the data. A third alternative is that you can specify your own target class prior probabilities. The list of probabilities must sum to 1. Prior probabilities are used during classification. For more discussion, see the documentation of the /PRIORS subcommand.
Pooled or separate
Should discriminant analysis use the pooled within-groups covariance matrix or should it use separate within-groups covariance matrices for classification? Technically, linear discriminant analysis...
