Question

What is the correct interpretation of the p-value in the hypothesis test conducted by the economist?

1) The p-value is less than the significance level, indicating that there is strong evidence to reject the null hypothesis.
2) The p-value is greater than the significance level, indicating that there is weak evidence to reject the null hypothesis.
3) The p-value is equal to the significance level, indicating that there is no evidence to reject the null hypothesis.
4) The p-value is not provided in the given information.

Answer 1

The correct interpretation of the p-value is that it is less than the significance level, indicating strong evidence to reject the null hypothesis.

Step-by-step explanation:

The correct interpretation of the p-value in a hypothesis test is option 1) The p-value is less than the significance level, indicating that there is strong evidence to reject the null hypothesis.

When the p-value is smaller than the significance level (commonly set at 0.05 or 0.01), it means that the observed test statistic is unlikely to have occurred if the null hypothesis is true. This provides significant evidence to reject the null hypothesis and support the alternative hypothesis. In contrast, if the p-value is larger than the significance level, it suggests weak evidence to reject the null hypothesis, indicating that the observed data could have happened by chance even if the null hypothesis is true.