2009-05-17_004415_regression_assignment

# 2009-05-17_004415_regression_assignment - Dear kzr1014...

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Dear kzr1014, Great questions! Chapter 12 12.48 In the following regression, X = weekly pay, Y = income tax withheld, and n = 35 McDonald’s employees. ANOVA table Source SS df MS F p-value Regression 387.6959 1 387.6959 8.35 .0068 Residual 1,533.0614 33 46.4564 Total 1,920.7573 34 R2 0.202 Std. Error 6.816 n 35 Regression output confidence interval variables coefficients std. error t (df = 33) p-value 95% lower 95% upper Intercept 30.7963 6.4078 4.806 .0000 17.7595 43.8331 Slope 0.0343 0.0119 2.889 .0068 0.0101 0.0584 a) Write the fitted regression equation. y=30.7963+0.0343x (b) State the degrees of freedom for a twotailed test for zero slope, and use Appendix D to find the critical value at a = .05. df=33 critical value = 2.035 (c) What is your conclusion about the slope? The slope is not 0. We reject the null hypothesis. (d) Interpret the 95 percent confidence limits for the slope. We are 95% confidence that the true slope falls between 0.0101 and 0.0584. (e) Verify that F = t2 for the slope. Sqrt(8.35) = 2.889. (f) In your own words, describe the fit of this regression. R^2 is only 0.202. Hence our predictor only explains 20.2% of the variability in our response. So while the model is significant, there is still a moderate amount of variability in y. 12.50 In the following regression, X = total assets (\$ billions), Y = total revenue (\$ billions), and n = 64 large banks.

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R2 0.519 Std. Error 6.977 n 64 ANOVA table Source SS df MS F p-value Regression 3,260.0981 1 3,260.0981 66.97 1.90E-11 Residual 3,018.3339 62 48.6828 Total 6,278.4320 63 Regression output confidence interval variables coefficients std. error t (df = 62) p-value 95% lower 95% upper Intercept 6.5763 1.9254 3.416 .0011 2.7275 10.4252 X1 0.0452 0.0055 8.183 1.90E-11 0.0342 0.0563 (a) Write the fitted regression equation. Y=6.5763 + 0.0453X
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2009-05-17_004415_regression_assignment - Dear kzr1014...

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