To address the question:

The P-value for the hypothesis test is 0.0304, and the significance level ($\alpha$) is 0.05.

Step-by-Step Explanation:

1. Compare the P-value with $\alpha$:

   • $P = 0.0304 < \alpha = 0.05$.

2. Decision Rule:

   • If $P < \alpha$, we reject the null hypothesis ($H_0$).
   • If $P \geq \alpha$, we fail to reject the null hypothesis ($H_0$).

3. Conclusion:

   • Since $P = 0.0304 < 0.05$, we reject the null hypothesis.

Correct Answer:

(a) Reject the null hypothesis.

Would you like a deeper explanation of hypothesis testing or any other related topic?

Here are 5 related questions to expand your understanding:

1. What does the P-value represent in hypothesis testing?
2. How does changing the significance level ($\alpha$) affect the conclusion of a hypothesis test?
3. What is the null hypothesis and the alternative hypothesis in this context?
4. What are Type I and Type II errors in hypothesis testing?
5. How can you calculate the P-value for a specific test statistic?

Tip: Always compare the P-value to the significance level to decide whether to reject or fail to reject the null hypothesis.