Marinan was looking at the output from a multiple regression model that her colleague had generated...

 

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Marinan was looking at the output from a multiple regression model that her colleague had generated in an effort to understand the company's overhead costs. The model included three cost drivers believed to be most related to these costs: number of supervisors, DL hours, and machine hours. Select output from the model is as follows. R Square 0.8624 P-value Coefficients Standard Error T-stat 18269.417 65135.16109 2.89044218 0.011863989 109.62454 800.6360844 0.13692181 0.893042169 80.0029618 15.95355316 5.01474255 0.000189272 5.16305359 0.750242342 6.88184777 7.5396E-06 Intercept Number of supervisors DL hours Machine hours Should Marinan and her colleague accept this model as is? If so, explain why it is valid. If not, explain why it is not valid and further identify what their next steps might be. Estimate time per unit under a learning curve. Marinan was looking at the output from a multiple regression model that her colleague had generated in an effort to understand the company's overhead costs. The model included three cost drivers believed to be most related to these costs: number of supervisors, DL hours, and machine hours. Select output from the model is as follows. R Square 0.8624 P-value Coefficients Standard Error T-stat 18269.417 65135.16109 2.89044218 0.011863989 109.62454 800.6360844 0.13692181 0.893042169 80.0029618 15.95355316 5.01474255 0.000189272 5.16305359 0.750242342 6.88184777 7.5396E-06 Intercept Number of supervisors DL hours Machine hours Should Marinan and her colleague accept this model as is? If so, explain why it is valid. If not, explain why it is not valid and further identify what their next steps might be. Estimate time per unit under a learning curve. Marinan was looking at the output from a multiple regression model that her colleague had generated in an effort to understand the company's overhead costs. The model included three cost drivers believed to be most related to these costs: number of supervisors, DL hours, and machine hours. Select output from the model is as follows. R Square 0.8624 P-value Coefficients Standard Error T-stat 18269.417 65135.16109 2.89044218 0.011863989 109.62454 800.6360844 0.13692181 0.893042169 80.0029618 15.95355316 5.01474255 0.000189272 5.16305359 0.750242342 6.88184777 7.5396E-06 Intercept Number of supervisors DL hours Machine hours Should Marinan and her colleague accept this model as is? If so, explain why it is valid. If not, explain why it is not valid and further identify what their next steps might be. Estimate time per unit under a learning curve.

Answer rating: 100% (QA)

Based on the given output it seems reasonable to accept the multiple regression model as is as it ha... View the full answer