Thank you in advance for help! I am conducting a study using General Linear Modeling on the distribution of financial aid at a college. I am not looking to project my findings onto a larger population. I only want to make statements/conclusions about this one school. The dataset has over 1000 students, each of whom were offered an scholarship.
My dependent variable (the scholarship award) is not normally distributed. The residuals of the model show non normal distribution and I have tried to take a log of my dependent variable... still not normally distributed.
Bootstrapping was suggested to me as a possible solution. Can someone help me understand if bootstrapping might change the nature of my data? Can I interpret the output of the GLM parameter estimates the same way?
Thank you very much.