1. The problem asks to state the hypothesis in each of the three tests. 2. In hypothesis testing, there are two hypotheses: the null hypothesis ($H_0$) and the alternative hypothesis ($H_a$). 3. The null hypothesis ($H_0$) usually represents the status quo or no effect. 4. The alternative hypothesis ($H_a$) represents what we want to test or prove. 5. The three common types of tests are: - Left-tailed test: $H_0: \mu = \mu_0$, $H_a: \mu < \mu_0$ - Right-tailed test: $H_0: \mu = \mu_0$, $H_a: \mu > \mu_0$ - Two-tailed test: $H_0: \mu = \mu_0$, $H_a: \mu \neq \mu_0$ 6. Here, $\mu_0$ is the hypothesized population mean. 7. These hypotheses set the framework for testing whether the sample data provides enough evidence to reject $H_0$ in favor of $H_a$. Final answer: - Left-tailed test: $H_0: \mu = \mu_0$, $H_a: \mu < \mu_0$ - Right-tailed test: $H_0: \mu = \mu_0$, $H_a: \mu > \mu_0$ - Two-tailed test: $H_0: \mu = \mu_0$, $H_a: \mu \neq \mu_0$