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CFA Level I · CFA Level I Exam · Estimation and Hypothesis Testing

Holding the sample and the test statistic constant, a researcher lowers the significance level of a test from 5% to 1%. The change will most likely:

Lowering the significance level from 5% to 1% decreases the probability of a Type I error but increases the probability of a Type II error. With a fixed sample, there is a trade-off, since a stricter rejection threshold makes false nulls harder to reject.

  1. Adecrease the probability of a Type I error and increase the probability of a Type II errorCorrect
  2. Bincrease the probability of a Type I error and decrease the probability of a Type II error
  3. Cdecrease both the probability of a Type I error and the probability of a Type II error

Explanation

The significance level equals the probability of a Type I error, so lowering it to 1% reduces that probability. With a fixed sample size, a stricter rejection region makes it harder to reject a false null, so the Type II error probability rises, and power falls.

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