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A pharmaceutical company ran a clinical trial to test if drug X cures disease Y. A statistician n...

A pharmaceutical company ran a clinical trial to test if drug X cures disease Y. A statistician named Z who is taking BIO 211 was given a task to perform a null hypothesis test. The test was perfect, and the null hypothesis was rejected at the alpha = 0.05 significance level. However, unbeknownst to Z, the company ran 39 extra clinical trials and secretly hired Z’s classmates to evaluate data obtained from each independent trial with the same null hypothesis test at the same significance level.

How could presumably independent data and independent hypothesis testing change the conclusion of a single test? Can you think of a strategy to fix this issue?

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