[unparagoned]

Men are only favourites by 1-2%. That's within the margin if error. Women are favourites by say 10% plus. The comment treats them the same, and base their theory on a binary concept. It's just bad logic and may even be a version of the Simpson paradox.

[sixo]

Women are the favorite by 10%+ only for a single department. This is a _different_ fallacy, now...

[YeGoblynQueenne]

I still do not understand. How are men "favourites by 1%-2%" and women "by 10% plus"? Favourites, for what?

And how did you calculate the margin of error for this study?

[unparagoned]

First each subject you compare the chance of admission. For men when they have a higher chance of admission, even in their most advantaged subject they have a higher chance of admission of 4%. Women on the other hand have a 20%. You can't say that they are equivalent in the least. In terms of error margins, a few percent is common, from experience. You could do a stats 95 confidence style calculation.

[YeGoblynQueenne]

You're talking about the difference between the percentages of applicants of each sex that were admitted. I tabulate:

                  Men              Women              % Difference
    Department Applied  Admitted Applied  Admitted    Men     Women
    A          [825]    62%      108      [82%]               +20%
    B          [560]    63%      25       [68%]               +5%
    C          325      [37%]    [593]    34%         +3%
    D          [417]    33%      375      [35%]               +2%
    E          191      [28%]    [393]    24%         +4%
    F          [373]    6%       341      [7%]                +1%

So, there's a 20% difference for one department that is a clear outlier and then everything is within a couple of percentiles of difference. In fact, the average difference is higher for men (3.5) than for women (2.666) ignoring the outlier, since it's an outlier.

However, I'm really not sure that taking the difference between proportions of different wholes is meaningful. The numbers don't add up to 100, so what does the difference mean, exactly?

I don't know what "a stats 95 confidence style" is, or how it is related to a margin of error, so please do that calculation and post your results.