1. **State the problem:** We are testing the hypothesis about the population mean $\mu$ with null hypothesis $H_0: \mu = 10$ and alternative hypothesis $H_a: \mu > 10$ at significance level $\alpha = 0.05$. 2. **Identify the test type:** Since the alternative hypothesis is $\mu > 10$, this is a right-tailed test. 3. **Test statistic formula:** For a mean test when population standard deviation is known or sample size is large, use the z-test: $$ z = \frac{\bar{x} - \mu_0}{\sigma / \sqrt{n}} $$ where $\bar{x}$ is the sample mean, $\mu_0 = 10$ is the hypothesized mean, $\sigma$ is population standard deviation, and $n$ is sample size. 4. **Decision rule:** Find critical value $z_{\alpha}$ for $\alpha=0.05$ in right tail. From z-tables, $z_{0.05} = 1.645$. 5. **Conclusion:** - If calculated $z > 1.645$, reject $H_0$. - Otherwise, do not reject $H_0$. Since no sample data is provided, we cannot compute $z$ or make a final decision. This completes the hypothesis test setup and decision criteria for the given problem.