A surgery center specializes in high-risk cardiovascular surgery. The center needs to forecast its profitability over the next three years to plan for capital growth projects. Find the distribution of the net present value of profit over the three-year horizon and analyze the summary statistics using 50 trials. Summarize your conclusions. Use a discount rate of 3%. Click here to view the descriptions of the model. Click here to view a sample of 50 simulation trial results. Set up a spreadsheet model and calculate the net present value for the profits in thousands of dollars using the minimum for uncertain values with uniform distributions, the mean for uncertain values with normal distributions, and the most likely values for uncertain values with triangular distributions. The net present value is $ thousand. (Round to the nearest thousand dollars as needed.) Based on the provided simulations, the mean net present value of the profits over the next three years is $[ (Round to the nearest thousand dollars as needed.) thousand, the standard deviation is $ thousand, the minimum is $ thousand, and the maximum is $ thousand. Model description For the first year, the anticipated number of patients served is uniform between 1,200 and 1,700. The growth rate for subsequent years is triangular with parameters (5%, 8%, 9%). and the growth rate for year 2 is independent of the growth rate for year 3. Average billing is normal with mean of $150,000 and standard deviation $12,000. However, because of managed care, the center collects only 30% of billings. Variable costs for supplies and drugs are calculated to be 10% of billings. Fixed costs for salaries, utilities, and so on will amount to $20,000,000 in the first year and the annual increase in fixed costs is uniform between 4% and 6% and independent of other years. Print Done Simulation Results Trial NPV 1 80,844 2 71,397 3 60,385 4 77,655 5 83,515 6 50,167 7 77,758 8 49,723 9 66,184 10 70,500 11 84,583 12 50,616 13 81,072 14 92,008 15 99,227 16 91,837 17 62,394 18 41,475 19 68,237 20 94,945 21 88,951 22 73,227 - X

The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned-ride snowmobiles. The model specifies that sales S vary jointly with disposable personal income Y and the population between ages 15 and 40, Z, and inversely with the price of the snowmobiles P. Based on past data, the best estimate of this relationship is S=kYZP where k has been estimated (with past data) to equal 100. If Y=11,000,Z=1,200, and P=20,000, what value would you predict for S? What happens if P is reduced to $17,500? How would you go about developing a value for k? What are the potential weaknesses of this model?

Furniture Forecasting Futura Furniture Products manufactures upscale office furniture for the Office of the Future. The sales division comprises regionally based sales offices made up of sales representatives and regional managers. Sales representativeswho report to the regional managersconduct direct sales efforts with customers in their regions. As part of the sales process, representatives gather information about likely future orders and convey that information back to the regional managers. Regional managers use that information to create sales forecasts, which are then used as the basis for manufacturing schedules. Sales representatives and regional managers are both compensated on a salary plus commission (percentage of revenue as pricing is centrally controlled). However, a regional managers commission is adjusted based on regional sales that exceed the forecasted budget. Corporate managers are concerned with one of Futuras key products, the DeskPod. They worry that DeskPod forecasts are inaccurate, causing extreme havoc in the manufacturing process. How are the forecasts likely to be inaccurate? What do you think is driving this inaccuracy? How might this problem be solved?

Estimate the double-log (log linear) time trend model for log cruise ship arrivals against log time. Estimate a linear time trend model of cruise ship arrivals against time. Calculate the root mean square error between the predicted and actual value of cruise ship arrivals. Is the root mean square error greater for the double log non-linear time trend model or for the linear time trend model?