A manufacturer of bedding wants to do quality control on its 400-thread-count sheets. The thread count should vary normally with a mean thread count u = 400 and a standard deviation o = 8. A quality control researcher randomly selects 16 sheets and finds that the mean thread count for the sample is 395.2. We want to determine if these data provide enough evidence to conclude that the mean thread count is significantly different from the target level. Which one of the two outputs represents the correct way to conduct this test? One-sample t-test t = -1.7235, df = 15, p-value = 0.1053 alternative hypothesis: true mean is not equal to 400 95% confidence interval: (389.3431, 401.1276) mean of x = 395.2354 O One-sample z-test of H = 400 vs. H # 400 assumed standard deviation = 8 n = 16 mean = 395.2 z-value = -2.4 two-tailed p-value = 0.0164 95% confidence interval: (396.0801, 403.9199)