MCQ 1 Which statement best describes a p-value in hypothesis testing? A. The probability that the null hypothesis is true B. The probability of observing results at least as extreme as the sample result, assuming the null hypothesis is true C. The probability that the alternative hypothesis is true D. The probability that the sample mean equals the population mean Correct answer: B Explanation: The p-value is calculated under the assumption that the null hypothesis is true. It tells you how surprising your result is if the null were correct, not whether the null is true.

MCQ 2 A test has sensitivity 0.90 and specificity 0.80. If you increase the decision threshold to label a result “positive,” which change is most likely? A. Sensitivity increases; specificity decreases B. Sensitivity decreases; specificity increases C. Both sensitivity and specificity increase D. Both sensitivity and specificity decrease Correct answer: B Explanation: A higher threshold makes it harder to call positives, so you miss more true cases (lower sensitivity). At the same time, you reduce false positives (higher specificity).

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