Explanation:
When the level of significance (α) is decreased:
Type I Error (α): This is the probability of rejecting the null hypothesis when it is actually true. Decreasing α directly reduces the probability of making a Type I error.
Type II Error (β): This is the probability of failing to reject the null hypothesis when it is actually false. Decreasing α typically increases β (the probability of Type II error), because the test becomes more conservative and less likely to reject the null hypothesis.
Power of the test (1-β): This decreases when α decreases, making the test less powerful at detecting false null hypotheses.
Analysis of options:
Therefore, option A is the correct answer.
Ultimate access to all questions.
When testing a hypothesis, which of the following statements is correct when the level of significance of the test is decreased?
A
The likelihood of rejecting the null hypothesis when it is true decreases.
B
The likelihood of making a Type I error increases.
C
The null hypothesis is rejected more frequently, even when it is actually false.
D
The likelihood of making a Type II error decreases.
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