Multiple regression. Bebe Williams wonders if she should run a multiple regression with both number of setups and number of setup hours, as cost drivers. If you want to use Excel to solve this problem, go to the Excel Lab at www.prenhall.com/hornqren/cost13e and download the template for Problem 10-38.

1. Run a multiple regression to estimate the regression equation for setup costs using both number of setups and number of setup hours as independent variables. You should obtain the following result

Regression 3: Setup costs = a + (b₁ × No. of setups) + (b₂ × No. of setup-hours)

2. Evaluate the multiple regression output using the criteria of economic plausibility goodness of fit, significance of independent variables, and specification of estimation assumptions. (Assume linearity, constant variance, and normality of residuals.)

3. What difficulties do not arise in simple regression analysis that may arise in multiple regression analysis? Is there evidence of such difficulties in the multiple regression presented in this problem? Explain.

4. Which of the regression models from problems 10-38 and 10-39 would you recommend Bebe Williams use? Explain.

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Standard Error $20,831 $132.02 $11.39 Variable -Value -0.19 Coefficient $3,895 Constant Independent variable 1: No. of setups Independent variable 2: No. of setup-hours 0.86; Durbin-Watson statistic = 1.36 $60.84 0.46 4.68 $53.30