The image appears to display a statistical question where the user is asked to determine whether to reject the null hypothesis $H_0$ at the $\alpha = 0.05$ significance level. To decide between "Reject" or "Do not reject," you would typically rely on the $p$-value from the test or a critical value comparison with the test statistic.

Could you provide the following information to finalize the decision?

1. The $p$-value obtained from the hypothesis test.
2. The test statistic value and the critical value (if applicable).
3. Any additional test context, such as the type of hypothesis test conducted (e.g., $t$-test, $z$-test).

Would you like a detailed explanation of how to approach this decision? If so, let me know! Below are related questions to expand your understanding.

Related Questions:

1. What is the relationship between $p$-values and the significance level $\alpha$?
2. How do critical values factor into rejecting or failing to reject $H_0$?
3. What assumptions are necessary for common hypothesis tests like $t$-tests or $z$-tests?
4. Can the null hypothesis ever be accepted, or is it always about rejection?
5. How does sample size impact the reliability of hypothesis testing?

Tip:

Always ensure your data meets the assumptions of the statistical test you are using before interpreting $p$-values or test statistics.