I am using "high school GPA" data as collected by a university as an independent variable in my dissertation research. At this particular institution, any GPAs above 4.0 (due to advanced placement credit, etc.) that are reported to the institution are truncated in the system to 4.0. Therefore, the distribution of the data now available to me has a significant ceiling effect and deviates from a normal curve. I will use this data in correlational analyses with student-performance in a specific course and with interval-level demographic data. I am interested in the significance of these correlations, so I really should have normally distributed data. Also, all the other independent variables I am using are normally distributed. I need to know what type of transformation would be appropriate for this situation. Or, is there another way (other than transforming the distribution) that I should be handling these analyses?

Any suggestions would be greatly appreciated.:yup: