In hypothesis testing, what does an alpha level of 0.05 imply?

An alpha level of 0.05 indicates that there is a 5% risk of rejecting the null hypothesis when it is actually true, signifying a 5% chance of making a Type I error. This means that if the null hypothesis is true, there is a 5% likelihood that the results of the test will suggest a statistically significant difference or effect, leading to an incorrect conclusion.

Additionally, the alpha level serves as the threshold for determining whether to reject the null hypothesis. When the p-value from the test is less than or equal to 0.05, researchers conclude that the evidence against the null hypothesis is strong enough to reject it in favor of the alternative hypothesis. Therefore, both statements are accurate: the alpha level represents the risk of claiming a difference when none exists and also establishes the criterion for rejecting the null hypothesis. This dual understanding of the alpha level justifies the selection of the correct answer.