Step 1 :(a) The null hypothesis $H_{0}$ and the alternative hypothesis $H_{1}$ for the test are as follows: \[ \begin{array}{l} H_{0}: \mu = 5 \\ H_{1}: \mu \neq 5 \end{array} \] The null hypothesis states that the mean pH of the new oranges is 5, as claimed by the grower. The alternative hypothesis states that the mean pH is not equal to 5, indicating that the grower's claim is incorrect. (b) To perform the hypothesis test, we will use the given sample mean, sample standard deviation, and sample size to calculate the test statistic using the formula provided: \[ t = \frac{\bar{x} - \mu}{\frac{s}{\sqrt{n}}} \] Given: - Sample mean ($\bar{x}$) = 5.1 - Population mean ($\mu$) = 5 (as per $H_{0}$) - Sample standard deviation (s) = 0.8 - Sample size (n) = 22 Plugging in the values, we get: \[ t = \frac{5.1 - 5}{\frac{0.8}{\sqrt{22}}} = \frac{0.1}{\frac{0.8}{\sqrt{22}}} = \frac{0.1}{0.1706} \approx 0.586 \] The degrees of freedom (df) for a t-test is equal to the sample size minus one, so df = 22 - 1 = 21. Since we are testing at the 0.10 level of significance and the alternative hypothesis is two-tailed, we need to find the critical t-value that cuts off an area of 0.05 in each tail (0.10 total). Using a t-distribution table or calculator, we find that $t_{0.05}$ with 21 degrees of freedom is approximately 1.721. Since the calculated t-value (0.586) is less than the critical t-value (1.721), we do not reject the null hypothesis. There is not enough evidence at the 0.10 level of significance to conclude that the mean pH of the new oranges is different from 5.