Step 1 :Given the following hypotheses: \(H_{o}: \mu=74.9\) and \(H_{a}: \mu<74.9\), with a significance level of \(\alpha=0.01\).
Step 2 :We have a sample of size \(n=17\) with mean \(\bar{x}=59.2\) and a standard deviation of \(s=20.2\).
Step 3 :First, we calculate the t-score using the formula: \(t = \frac{\bar{x} - \mu}{s / \sqrt{n}}\).
Step 4 :Substituting the given values into the formula, we get: \(t = \frac{59.2 - 74.9}{20.2 / \sqrt{17}} \approx -3.2046\).
Step 5 :Next, we calculate the p-value. The p-value is the probability of observing a t-score as extreme as the one calculated (or more extreme) under the null hypothesis.
Step 6 :Using a t-distribution table or a statistical software, we find that the p-value is approximately 0.0028.
Step 7 :Since the p-value is less than the significance level \(\alpha=0.01\), we reject the null hypothesis.
Step 8 :Final Answer: The p-value for this sample is approximately \(\boxed{0.0028}\). Since the p-value is less than the significance level \(\alpha=0.01\), we \(\boxed{reject the null hypothesis}\).