Answer: Type II error.

## Explanation This question tests understanding of Type I and Type II errors in hypothesis testing. **Key Concepts:** 1. **Type I Error (α error)**: Rejecting a true null hypothesis (false positive) 2. **Type II Error (β error)**: Failing to reject a false null hypothesis (false negative) 3. **Power of a test**: Probability of correctly rejecting a false null hypothesis (1 - β) **Analysis:** - The scenario describes "fails to reject a false null hypothesis" - This is the exact definition of a Type II error - A Type I error would be "rejecting a true null hypothesis" - While a test with little power is more likely to make Type II errors, the specific result described is a Type II error itself **Correct Answer:** B (Type II error) **Additional Context:** - Type I error rate is denoted by α (significance level) - Type II error rate is denoted by β - Power = 1 - β (probability of correctly rejecting false null) - The relationship between errors: Decreasing α (Type I error) typically increases β (Type II error) for a given sample size

Author: LeetQuiz .