Here is an easy one. I have a group of rodent skulls. They are from several named groups which are also geographic regions. One group is classified as "unknown". I have metric data and used Discriminant Analysis and a plot of the Canonical 1 and 2 scores. And, using the values in the Discriminant Scores table to show predictions.
I also have categorical data. Briefly, things like the number of holes in the skull for nerves and veins. They vary geographically from 2 to 4 (e.g. 1 on one side, a double hole on the other side). I am looking at the data in the Fit Y by X analysis. This is showing me Mosaic Plots and chi square tests for each variable. I need to retrace my steps, but some command also compares means with a student t test such that groups that are statistically different are labeled A, b, C, etc. Any advice there would be appreciated.
However, I would like to find a statistically valid test for classifying the unknown group on these categorical variables. Or, at least create a table suggesting greatest similarity as a group, not as individuals. I know there is a clustering method, but not clear to me how to use this for groups rather than individuals.