LizzyM Linear Regression

The MCAT/GPA grid gives US MD acceptance rates for various MCAT/GPA ranges. I performed linear regression in R on acceptance rate (AR) vs MCAT (502 to 517) and GPA (3.00 to 4.00). The MCAT bounds are because the lowest median MCAT on MSAR is 500 and because the granularity of the grid drops off past 517. The GPA lower bound is because the lowest median GPA on MSAR is 3.1. Here is the model:

AR = 32.99 * GPA + 2.53 * MCAT - 1362.00, R^2 = 0.95

Dividing the GPA coefficient by the MCAT coefficient yields 13.03. The LizzyM score is 10 * GPA + MCAT. However, if we account for the fact that the new MCAT has a score range of 528 - 472 = 56 and the old MCAT has a score range of 45 - 3 = 42, we get an updated LizzyM GPA/MCAT ratio of 10 * 56/42 = 13.33. Overall, the linear model seems to align with the LizzyM score. Note that this model breaks down for high stats; it predicts a 4.0/528 would have a 105.80% acceptance rate, which is false.

TLDR: For the majority of US MD applicants (GPA 3.00 to 4.00 and MCAT 502 to 517), the LizzyM score effectively relates GPA and MCAT in the context of predicting admissions chances.