Perform a chi-square test on this data to see if there is evidence for an association between gender and acceptance into one of these top six graduate programs.
Men
-------Women
-------Total
-------Admitted 1195 559 1754 Denied 1486 1276 2762 Total 2681 1835 4516
Answer: The admittance rate is different based on gender P < 0.0005.
The next table calls into question the results of the previous exercise. Here is a breakdown by program. (Note: there are now three variables being displayed: gender, status (accepted or denied) and program that makes this a type of 3-way table.)
Men
Accepted
-------Men
Denied
------Acceptance
Rate
--------||
||
||Women
Accepted
-------Women
Denied
------Acceptance
Rate
--------Program A 511 314 61.94% || 89 19 82.41% Program B 352 208 62.86% || 17 8 68.00% Program C 120 205 36.92% || 202 391 34.06% Program D 137 270 33.66% || 132 243 35.20% Program E 53 138 27.75% || 95 298 24.17% Program F 22 351 5.90% || 24 317 7.04%
While it is not always the case that an association revealed by the chi-square test is due to some lurking variable, when it is (as was the case here with the lurking variable Program), the chi-square test cannot be expected to account for it.