The correct answer is:

D. Fail to reject the null hypothesis because the​ P-value is greater than the significance level, alpha (α).

Explanation:

• If the P-value is greater than the significance level (α), it means there is not enough evidence to reject the null hypothesis. Therefore, you "fail to reject" the null hypothesis.
• If the P-value is less than or equal to the significance level (α), you would reject the null hypothesis.

Would you like further details or have any questions?

Here are 5 related questions:

1. What is a P-value in hypothesis testing?
2. How do you choose the significance level (α) for a test?
3. What are Type I and Type II errors in hypothesis testing?
4. How does the sample size affect the P-value in hypothesis testing?
5. What is the relationship between confidence intervals and hypothesis testing?

Tip: Always check the significance level (α) before making a conclusion about the null hypothesis, as it sets the threshold for decision-making.