Final answer:
If the null hypothesis is really false, with a beta of 0.75, there is a 75% chance that the statistical decision will be to fail to reject the null hypothesis, referring to a Type II error.
Step-by-step explanation:
The student's question pertains to the concept of Type II error (beta) in the context of hypothesis testing. When we assume that alpha is 0.05 and beta is 0.75, this means we have a 5% risk of incorrectly rejecting a true null hypothesis (Type I error) and a 75% chance of failing to reject a false null hypothesis (Type II error). Thus, if the null hypothesis is really false, the probability that the statistical decision will be to fail to reject the null is beta, which equals 0.75 or 75%.