# Using the chi-square to illuminate the gray areas:

In the last two examples (42% and 90%), it was pretty obvious what the chi-square test would say. In this last case, where 50% of sick days fall on M/F, it's not so obvious. This is a case where the statistical test can help resolve a gray area. Here goes...

**You should have gotten a chi-square-calc of 4.166, compared to the chi-square-crit of 3.84. So, its a close call, but the test says that Dilbert's random sickday model probably does NOT hold up. **The test can't tell you this for sure, but it still gives you an objective way to say "(probably) yes" or "(probably) no" when you're in a "gray" area.

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