Multiple regression (continuation of 10-38) Bebe Williams wonders if she should run a multiple regression with both number of setups and number of setup-hours, as cost drivers.

Required

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.

Transcribed Image Text:

Standard Error Variable t-Value Coefficient -$2,807 $ 58.62 Constant Independent variable 1: No. of setups Independent variable 2: No. of setup-hours r = 0.86; Durbin-Watson statistic = 1.38 $34,850 $ 133.42 13.08 -0.08 0.44 4.00 $ 52.31