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2.5 Female children FIGURE 23.1 Estimated Treatment Means Plot-Growth Hormone Example 2.0 Male children Change in Growth Rate 1.SE 1.0 0 Severely depressed Moderately depressed

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2.5 Female children FIGURE 23.1 Estimated Treatment Means Plot-Growth Hormone Example 2.0 Male children Change in Growth Rate 1.SE 1.0 0 Severely depressed Moderately depressed Bone Development Mildly depressed *22.7. Refer to Productivity improvement Problem 16.7. The economist also has information on annual productivity improvement in the prior year and wishes to use this information as a concomitant variable. The data on the prior year's productivity improvement (Xy) follow. 2 3 4 5 6 7 8 9 10 11 12 1 8.2 7.9 7.0 5.7 7.2 7.0 6.5 7.9 6.3 2 8.8 10.0 10.7 10.0 9.7 9.4 10.6 9.8 10.0 10.3 8.9 10.0 3 11.5 12.2 12.8 11.0 12.3 12.1 a. Obtain the residuals for covariance model (22.3). b. For each treatment, plot the residuals against the fitted values. Also prepare a normal probability plot of the residuals and calculate the coefficient of correlation between the ordered residuals and their expected values under normality. What do you conclude from your analysis? c. State the generalized regression model to be employed for testing whether or not the treatment regression lines have the same slope. Conduct this test using a =.01. State the alternatives, decision rule, and conclusion. What is the P-value of the test? 2.5 Female children FIGURE 23.1 Estimated Treatment Means Plot-Growth Hormone Example 2.0 Male children Change in Growth Rate 1.SE 1.0 0 Severely depressed Moderately depressed Bone Development Mildly depressed *22.7. Refer to Productivity improvement Problem 16.7. The economist also has information on annual productivity improvement in the prior year and wishes to use this information as a concomitant variable. The data on the prior year's productivity improvement (Xy) follow. 2 3 4 5 6 7 8 9 10 11 12 1 8.2 7.9 7.0 5.7 7.2 7.0 6.5 7.9 6.3 2 8.8 10.0 10.7 10.0 9.7 9.4 10.6 9.8 10.0 10.3 8.9 10.0 3 11.5 12.2 12.8 11.0 12.3 12.1 a. Obtain the residuals for covariance model (22.3). b. For each treatment, plot the residuals against the fitted values. Also prepare a normal probability plot of the residuals and calculate the coefficient of correlation between the ordered residuals and their expected values under normality. What do you conclude from your analysis? c. State the generalized regression model to be employed for testing whether or not the treatment regression lines have the same slope. Conduct this test using a =.01. State the alternatives, decision rule, and conclusion. What is the P-value of the test

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