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    Question

    In hypothesis testing, which of the following best

    describes the p-value?
    A The probability that the null hypothesis is true Correct Answer Incorrect Answer
    B The probability of obtaining the observed results, assuming the null hypothesis is true. Correct Answer Incorrect Answer
    C The likelihood of rejecting the null hypothesis when it is false Correct Answer Incorrect Answer
    D The threshold for rejecting the null hypothesis Correct Answer Incorrect Answer
    E The proportion of variation explained by the independent variable. Correct Answer Incorrect Answer

    Solution

    The p-value quantifies how likely it is to observe the sample data (or more extreme results) under the assumption that the null hypothesis is correct. A low p-value (e.g., <0.05) suggests that the observed data is unlikely under the null hypothesis, leading to its rejection in favor of the alternative hypothesis. For example, if testing a new drug, a p-value of 0.03 indicates a 3% chance that the observed effect is due to random variation under the null hypothesis. Why Other Options Are Wrong : A) The p-value doesn’t measure the truth of the null hypothesis itself. C) This describes the power of a test, not the p-value. D) The threshold (e.g., 0.05) is set by the researcher; it’s not the p-value. E) This describes R-squared in regression analysis, not hypothesis testing.

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