Final answer:
The risk related to the efficiency of testing is the risk of incorrect acceptance, which is known as a Type II error. This occurs when a false null hypothesis is not rejected, leading to inefficiency in testing as a real effect or relationship is incorrectly assumed not to exist.
Step-by-step explanation:
The risks related to the efficiency of testing in the context of statistical hypothesis testing are Type I and Type II errors. A Type I error, also known as alpha (α), occurs when the null hypothesis (H0) is rejected even though it is true. On the other hand, a Type II error, designated by beta (β), happens when the null hypothesis is not rejected, even though it is actually false in reality. According to the provided choices and scenarios, concerning the efficiency of testing, the risk of incorrect acceptance (which is the same as not rejecting a false null hypothesis) corresponds to the Type II error. Incorrect acceptance would negatively affect the efficiency of testing since it would lead the researcher to believe that a particular effect or relationship does not exist when, in fact, it does.