is the failure to reject a false null hypothesis.

is the failure to reject a false null hypothesis. Options: (a) Type I error (b) Type A error (c) Type II error (d) Type B error ✅ Correct Option: (c) Type II error Explanation (200+ words): A Type II error occurs when a researcher fails to reject a null hypothesis that is actually false. This means that a real effect, difference, or relationship exists in the population, but the statistical test fails to detect it. Type II errors are often caused by small sample sizes, low statistical power, or high variability in data. In hypothesis testing, while researchers are often concerned about Type I errors, Type II errors are equally important because they can lead to incorrect conclusions that no effect exists. The probability of making a Type II error is denoted by β (beta). Reducing β increases the power of a test, which is the probability of correctly rejecting a false null hypothesis. 10 PPSC-Related Facts: 1. Type II = false negative 2. Symbolized by β 3. Fails to detect true effect 4. Related to statistical power 5. Reduced by larger samples 6. Opposite of Type I error 7. Common in hypothesis testing 8. Important decision error 9. Exam-frequent concept 10. Impacts research validity