1. The problem asks: What is the p-value? 2. The p-value is a measure used in hypothesis testing to determine the strength of the evidence against the null hypothesis. 3. The formula for the p-value depends on the test statistic and the distribution under the null hypothesis. Generally, it is the probability of observing a test statistic as extreme or more extreme than the one observed, assuming the null hypothesis is true. 4. Important rules: - A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, so you reject the null hypothesis. - A large p-value (> 0.05) indicates weak evidence against the null hypothesis, so you fail to reject the null hypothesis. 5. Without specific data or test statistic, the exact p-value cannot be calculated here. 6. To find the p-value, you need: - The test statistic value - The type of test (e.g., z-test, t-test) - The distribution of the test statistic under the null hypothesis 7. Then, use statistical tables or software to find the p-value corresponding to the test statistic. In summary, the p-value quantifies how likely your observed data would occur if the null hypothesis were true.