<p>OK, here’s another math wrinkle. Positive and negative numbers that you generate from the formula in Post #40 above aren’t directly comparable. For example, a score of +10% means male favoritism, and a score of -10% means female favoritism – but not to the same degree. A school scoring +10% is not the “opposite” of a school scoring -10%. Sp “double-digit” scores don’t have the same meaning if positive and negative values are being compared.</p>
<p>Suppose School A has a 40% acceptance rate for men, and a 25% rate for women. Suppose School B has exactly opposite rates: 25% for men, 40% for women. If you work through the math, you will get a score of +60% for School A, but -37.5% for School B. For purposes of your rating, you would probably want School A and School B to generate the same scores, except with opposite signs. </p>
<p>If you want to compare schools that favor men vs. schools that favor women, it would be better to use two different formulas. </p>
<p>Use (M / F * 100) - 100 at schools that favor men
Use (-1) * (F / M * 100) - 100 at schools that favor women </p>
<p>The -1 is arbitrarily included in the second formula, so that schools that favor women will get negative scores. Schools that favor men will get positive scores. </p>
<p>With these formulas, Schools A and B have exactly opposite acceptance rates and exactly opposite scores: +60% at School A and -60% at School B. </p>
<p>If you use this approach, Harvey Mudd gets a score of -78.8%. Harvey Mudd actually favors women to an even greater extent than Pomona (+59.8 %) favors men. In fact, the most extreme differences in gender acceptance rates may well be the female favoritism shown by some tech schools. For example, MIT and Caltech would both get triple-digit negative scores (< -100%), because the female acceptance rates are more than double the male acceptance rates.</p>