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CAN I GET ANSWERS FOR B AND C PLSS Cost Modeling. General Widget Corporation has collected data on the daily output and daily production cost

CAN I GET ANSWERS FOR B AND C PLSS
Cost Modeling. General Widget Corporation has collected data on the daily output and daily
production cost of widgets produced at its factory. (Data for the study are shown in the table below.) The company
believes that daily output (DO) and daily production cost
(PC) ought to be linearly related. Thus, for some numbers
a and b:
image text in transcribed
for the study are shown in the table below.) The company believes that daily output (DO) and daily production cost (PC) ought to be linearly related. Thus, for some numbers a and b : PC=a+bDO a. Build a least-squares model to estimate the parameters a and b in the linear relationship. In other words, minimize the sum of squared differences between the model's predicted values and the observations. What are the best values of the parameters a and b for this criterion? What is the minimum value of the objective function? (Verify your results by using Excel's Regression tool.) b. Suppose, instead, that a better criterion is thought to be minimizing the sum of absolute deviations between the model's predicted values and the observations. What are the best values of the parameters a and b for this criterion? What is the minimum value of the objective function? c. Suppose, instead, that a better model than the linear model is thought to be the power function PC=a(DO)b for the study are shown in the table below.) The company believes that daily output (DO) and daily production cost (PC) ought to be linearly related. Thus, for some numbers a and b : PC=a+bDO a. Build a least-squares model to estimate the parameters a and b in the linear relationship. In other words, minimize the sum of squared differences between the model's predicted values and the observations. What are the best values of the parameters a and b for this criterion? What is the minimum value of the objective function? (Verify your results by using Excel's Regression tool.) b. Suppose, instead, that a better criterion is thought to be minimizing the sum of absolute deviations between the model's predicted values and the observations. What are the best values of the parameters a and b for this criterion? What is the minimum value of the objective function? c. Suppose, instead, that a better model than the linear model is thought to be the power function PC=a(DO)b

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