In statistical hypothesis testing, errors are classified based on the actual status of the null hypothesis (H0) and the decision made. Which configuration correctly defines Type I and Type II errors?

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Mathematics · Biostatistics

Verified Solution4 OptionsUpdated: October 2026👁️1 View

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Correct answer

Rejecting H0 when H0 is true is a Type I error; Failing to reject H0 when H0 is false is a Type II error.

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Answer 1

Rejecting H0 when H0 is false is a Type II error; Failing to reject H0 when H0 is false is a Type I error.

Answer 2

Failing to reject H0 when H0 is true is a Type I error; Rejecting H0 when H0 is true is a Type II error.

Answer 3

Rejecting H0 when H0 is true is a Type I error; Failing to reject H0 when H0 is false is a Type II error.

Answer 4

Rejecting H0 when H0 is false is a Type I error; Accepting H0 when H0 is true is a Type II error.

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