A computer randomly selected 80 university students 200 times. The percentages of females in each sample are plotted below. What do these results suggest, if it is known that exactly 50% of the student body are female?

Sorry, this is a literature site. I'm not sure how helpful I would be with this question.

With 80 students per sample and a true female proportion of 50%, the sample percentages should generally cluster around 50%, with some variation from sample to sample. The standard error is sqrt(0.5 × 0.5 / 80) ≈ 5.6 percentage points, so most samples should fall fairly close to 50%, while larger deviations are less common. The 200 samples show how random sampling produces variation even when the underlying population proportion stays fixed. The same idea applies to planning university schedules. If you are balancing attendance requirements across several classes, an attendance calculator helps track how many sessions you need to attend before reaching a required percentage.

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I like how this question uses repeated random samples to show that even when the true percentage is 50%, individual samples can vary quite a bit. It’s a simple way to make sampling variability feel much more concrete. That idea of seeing small changes add up reminds me of Merge Fruit where each move can shift the whole board. It’s a fun one to try when you have a few minutes.