Testwise Alpha Level describes what?

Testwise Alpha Level describes what?

• A. The risk of a Type II Error, or alpha level, for an individual hypothesis test.
• B. The risk of a Type I Error, or alpha level, for an individual hypothesis test.
• C. The overall chance of a Type I error across all tests.
• D. The threshold p-value for significance in the entire study.

Answer: (B)

Testwise alpha level is the probability of making a Type I error on an individual hypothesis test. It’s set before you analyze data and acts as the decision rule for that test: if the p-value is at or below alpha, you reject the null for that test. For example, an alpha of 0.05 means you’re willing to accept a 5% chance of a false positive on this single test. This is different from the risk of a Type II error, which relates to missing a real effect and is governed by beta, not alpha. It’s also different from the overall chance of a Type I error across multiple tests, which is called the family-wise (or experiment-wise) error rate and tends to be higher as more tests are conducted. The idea of a single threshold for significance across the entire study misstates the per-test nature of alpha, though researchers may adjust per-test thresholds to control the overall error rate when many tests are used.

Testwise alpha level is the probability of making a Type I error on an individual hypothesis test. It’s set before you analyze data and acts as the decision rule for that test: if the p-value is at or below alpha, you reject the null for that test. For example, an alpha of 0.05 means you’re willing to accept a 5% chance of a false positive on this single test. This is different from the risk of a Type II error, which relates to missing a real effect and is governed by beta, not alpha. It’s also different from the overall chance of a Type I error across multiple tests, which is called the family-wise (or experiment-wise) error rate and tends to be higher as more tests are conducted. The idea of a single threshold for significance across the entire study misstates the per-test nature of alpha, though researchers may adjust per-test thresholds to control the overall error rate when many tests are used.