I am looking at this paper by the College Board on the validity of SAT score and High School GPA (HSGPA) for First Year GPA (FYGPA). They state they are using a straight forward linear regression to analyse the data. However, I have a question about how a correlation is affected by a couple of factors for these examples:
- Does the fact that the SAT score is a enforced normal distribution and GPA is not likely a normal distrubution affect the validity of the correlation?
- Should they report whether they are using normalized scores and does the lack of reporting mean that the different scales were not normalized?
- Does the difference in the distribution mean that the variance will be skewed? In other words, doesn't the fact that one metrics is forced normal distribution and the other is not imply a heteroskedasticity that makes a simple linear regression not the best tool for comparing these sets. So looking at the below picture which is representative of the distributions I can see how a linear regression can go from HS GPA to College GPA and still have an even distrubution. However, going from a perfect normal curve to totally skewed distribution with a linear colleration would have to have a very variance at the edges (upper part error will be below line while lower part error will be above line).