The short answer: I don't think you want to trust those results. Only continuous variables should be used as Y variables in discriminant analysis.
The longer answer: Discriminant analysis requires continuous Ys and a categorical X. In JMP, data table columns have both a data type and a modeling type (see here for the difference), and it looks like you have some columns with a numeric data type but a nominal or ordinal modeling type, meaning that while they're represented by numbers in the data table, they're really not continuous variables. Sex could be a good example: It may be represented as 0 and 1 in the table but really is nominal (male = 0 and female = 1). The discriminant analysis launch dialog will allow you to input Sex as a Y variable due to the numeric data type but thankfully throws up this warning if Sex is set to a non-continuous modeling type. (If you were to change Sex's data type to character, then the launch dialog would reject it outright when you try to put it in the Y role.) Including a non-continuous numeric column as a Y in discriminant analysis should be done only when you believe the variable can be treated as a continuous variable for the purposes of this specific analysis.
Ross Metusalem
JMP Academic Ambassador
