As @PaigeMiller notes, you can use the GLM procedure to fit an analysis of variance (ANOVA) as long as the residuals from the model follow a normal distribution and, I will add, as long as each observation is independent of other observations (in other words, you have no clustering, repeated measures, blocking, etc.).
I will also add that if your total sample size is only 30 students, you almost surely will not be able to include all seven of your independent variables simultaneously in one model because you do not have enough data to support estimation of all the parameters. Rules of thumb for a good number of observations range from 5 to 10 to 20 or even 30 observations per parameter estimate. For each categorical independent variable, the number of parameter estimates will be equal to the number of levels minus one. Depending on your analysis objectives, you will need to use some form of model selection, for example LASSO selection in the GLMSELECT procedure, or selection based on AIC or some other information criterion.
I hope this helps.
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