Selecting an alpha level involves balancing the risk of a Type I error (rejecting a true null hypothesis), with common values like 0.05, 0.01, or 0.001 used to control this risk. However, lowering the alpha level makes it harder to detect a true treatment effect, as the critical region boundaries move further out, requiring stronger evidence to reject the null hypothesis.
