To determine the correct conclusion regarding the null hypothesis $H_0$, we need to compare the given $P$-value (0.0131) with the significance level $\alpha$ (0.05).

The decision rule is as follows:

• Reject $H_0$ if the $P$-value is less than or equal to $\alpha$.
• Fail to reject $H_0$ if the $P$-value is greater than $\alpha$.

Given:

• $P$-value = 0.0131
• $\alpha = 0.05$

Since $0.0131 < 0.05$, we reject $H_0$.

Conclusion:

The correct answer is: D. Reject $H_0$ because the $P$-value is less than or equal to $\alpha$.

Would you like further details on interpreting $P$-values or have any other questions?

Here are some related questions you might find helpful:

1. What is the meaning of a significance level in hypothesis testing?
2. How does the $P$-value relate to the likelihood of observing the sample result under the null hypothesis?
3. What are the possible outcomes and implications of rejecting $H_0$?
4. How would the conclusion change if the $P$-value were 0.06 instead of 0.0131?
5. Why is it important to set a significance level before conducting a hypothesis test?

Tip: Always compare the $P$-value with the significance level to determine whether to reject the null hypothesis; this comparison is fundamental in hypothesis testing.