Question 1:
The Decision Science Department is trying to determine whether to rent a slow or a fast copier. The department believes that an employee's time is worth $15 per hour. The slow copier rents for $4 per hour, and it takes an employee an average of 10 minutes to complete copying. The fast copier rented for $15 per hour and it takes an employee an average of six minutes to complete copying. On average, four employees per hour need to use the copying machine. (Assume the copying times and inter arrival times to the copying machine are exponentially distributes.) Which machine should the department rent to minimize expected total cost per hour?
Question 2:
A power company located in souther Alabama wants to predict the peak power load (i.e., the maximum amount of power that must be generated each day to meet demand) as a function of the daily high temperature (X). A random sample of 25 summer days is chosen, and the peak power load and high temperature are recorded each day.
a) Create a scatterplot for these data. Comment on the observed relationship between Y and X.
b) Estimate an appropriate regression equation to predict the peak power load for this power company. Interpret the estimated regression coefficients.
c) Analyze the estimated equation's residuals. Do they suggest that the regression equation is adequate? If not, return to part b and revise your equation. Continue to revise the equation until the results are satisfactory.
d) Use your final equation to predict the peak power load on a summer day with a high temperature of 100 degrees.
Question 3:
a) Assume that the only factor influencing monthly sales is adervitising. Fit the following two curves to these data: linear (Y=a+bX) and power (Y=aXb). Which equation best fits the data?
b) Interpret the best-fitting equation.
c) Using the best-fitting equation, predict sales during a month in which $60,000 is spent on advertising.
Attachment:- Question.xlsx