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# src="/qa/attachment/10699006/" alt="Screen Shot 2019-10-01 at 6.34.24 PM.png" />question 15,16,17 Attachment 1 Attachment 2 ATTACHMENT PREVIEW Download attachment Screen Shot 2019-10-01 at 6.34.24 PM.png Table 3.13 Data for the Trout Experiment Code Hemoglobin (grams per 100I ml]I 1 6.? 7.8 5.5 8.4 ?.0' ?.8 8.6 ?.4 5.8 7.0 2 9.9 8.4 10.4 9.3 10.? 11.9 ?.1 6.4 8.6 10.6 3 10.4 8.1 10.6 8.? 10.? 9.1 8.8 8.1 228 8.0 4 9.3 9.3 7.2 ?.8 9310.2 8.? 8.6 9.3 7.2 Source: GutsellJ. 5. {1951). Copyright ® 1951 International Biometric Society. Reprinted with permission. The ﬁsh food added to the troughs contained, respectively, 0, 5, 10, and 15 grams of sulfamerazine per 100 pounds of ﬁsh (coded l, 2, 3, 4). The measurements were made on ten randomly selected ﬁsh from each trough after 35 days. (a) Plot the data and comment on the results. (b) Write down a suitable model for this experiment. (c) Calculate the least squares estimate of the mean response for each treatment. Show these estimates on the plot obtained in (a). Can you draw any conclusions from these estimates? (d) Test the hypothesis that sulfameraziue has no eﬂect on the hemoglobin content of trout blood. (e) Calculate a 95% upper conﬁdence limit for 0'2. 16. &quot;It-out experiment, continued Suppose the trout experiment of Exercise 15 is to be repeated with the same I: = 4 treatments , and suppose that the same hypothesis, that the treatments have no effect on hemoglobin content. is to be tested. (a) For calculating the number of observations needed on each treatment, what would you use as a guess for 0'2? (b) Calculate the sample sizes needed for an analysis of variance test with or = 0.05 nnJ— .nlu .. J— ”n ATTACHMENT PREVIEW Download attachment Screen Shot 2019-10-01 at 6.34.59 PM.png (b) Calculate the sample sizes needed for an analysis of variance test with a = 0.05 to have power 0.95 if (i) A = 1.5. (ii) A = 1.0. (iii) A = 2.0. 17. Soap experiment, continued In Example 3.6.2, page 53, a sample size calculation was made for the number of observations needed to detect, with probability (0.25) = 0.90, a difference in weight loss of at least A = 0.25 grams in v = 3 difference types of soap, using an analysis of variance with a probability of a = 0.05 of a Type I error. The calculation used an estimate of 0.007 grams for o and showed that r = 4 observations were needed on each type of soap. The experiment was run with r = 4, and the least squares estimate for o was 0.0772. If the true value for o was, in fact, 0.08, what power did the test actually have for detecting a difference of A = 0.25 grams in the weight loss of the three soaps?

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