15. The Vision Hospital is considering the purchase of a new Advance Scan machine. The decision will rest partly on the anticipate patients in the coming months. The numbers of patents during the past years are as follows: Year Number of patents(Actual) 1600 2200 2600 2800 2016 2017 2018 2019 2020 3100 Compute the forecast for the year 2021 using exponential smoothing with a forecast for the year 2016 of 1500 and a = 3

15. The Vision Hospital is considering the purchase of a new Advance Scan machine. The decision will rest partly on the anticipate patients in the coming months. The numbers of patents during the past years are as follows: Year Number of patents(Actual) 1600 2200 2600 2800 2016 2017 2018 2019 2020 3100 Compute the forecast for the year 2021 using exponential smoothing with a forecast for the year 2016 of 1500 and a = 3

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section: Chapter Questions

Problem 40P: The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels....

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The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.
Under what conditions might a firm use multiple forecasting methods?
The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?
4 Trinity General Hospital had the following number of patient admissions during the past 8 weeksWeek Patient Admissions1 1202 1453 954 1125 1306 1107 1008 140 a. Develop a 3-week weighted average forecast forWeek 4 through 9 with weightsW1 = 0.2W2 = 0.3W3 = 0.5 b. Forecast patient admissions for week 9 using simpleexponential smoothing with α = 0.2. Assume that the forecast for Week 2 (F2) is the naïve forecast.
A distributor uses the following equation for forecasting demand of ski goggles: Y = 834 + 18*t, where t=0 in Spring of 2013. Each season is a period, so Summer 2013 would be t=1. His seasonal relatives are (Fall=1.2; Winter=1.4; Spring = 0.9; Summer= 0.8). What is his seasonalized forecast for Spring 2014? Plz do fast asap
A police station had to deploy police officers for emergencies multiple times the lastfour evenings. The numbers of emergencies for Monday, Tuesday, Wednesday, andThursday were 7, 4, 8, and 11, respectively. What would be the station’s forecast for theemergencies on Friday using a two-day moving average approach
The table shows the values found in the error analysis. What method of forecasting would be best to use? What is the forecasted value? MSE forecast for week 13 Time Series 1.08 14.76 3-week MA 3.04 13.67 exp smoothing 11.04 9.5 Group of answer choices A.) Time Series, forecasted value = 14.76 B.) 3-week MA, forecasted value = 13.67 C.) exp smoothing, forecasted value = 9.5 D.) Time Series, forecasted value = 1.08 E.) 3-week MA, forecasted value = 3.04 F.) exp smoothing, forecasted value = 11.04
Winter’s method is being used to forecast quarterlyU.S. retail sales (in billions of dollars). At the end of the firstquarter, Lt 300, Tt 30, and the seasonal indexes are asfollows: quarter 1, 0.90; quarter 2, 0.95; quarter 3, 0.95;quarter 4, 1.20. During the second quarter, retail sales are$360 billion. Assume a 0.2, b 0.4, and g 0.5.a At the end of the second quarter, develop a forecastfor retail sales during the fourth quarter of the year.b At the end of the second quarter, develop a forecastfor the second quarter of the following year.
Holiday Lodge The Holiday Lodge is a large hotel and casino in the Adirondacks. The relatively new hotel is two years old, and the manager is trying to develop a plan to staff the maintenance department. The hotel’s manager wants to use the two years of data below to forecast one month ahead of maintenance calls. The data is provided in the spreadsheet named HOLIDAY LODGE DATA.XLS Month Calls 1 46 2 39 3 28 4 21 5 14 6 16 7 14 8 13 9 9 10 13 11 18 12 15 13 12 14 6 15 19 16 9 17 12 18 14 19 16 20 12 21 13 22 9 23 14 24 15 Develop a forecast for month 25 using a 4 month moving average, exponential smoothing (a = 0.2) and regression. Which forecast is preferred? Why?
Tom Glass forecasts electrical demand for the FlatlandsPublic Power District (FPPD). The FPPD wants to take itsComstock power plant out of service for maintenance whendemand is expected to be low. After shutdown, performingmaintenance and getting the plant back on line takes twoweeks. The utility has enough other generating capacity tosatisfy 1,550 megawatts (MW) of demand while Comstockis out of service. Table 8.5 shows weekly peak demands(in MW) for the past several autumns. When next in year 6should the Comstock plant be scheduled for maintenance?
Tom Glass forecasts electrical demand for the FlatlandsPublic Power District (FPPD). The FPPD wants to take itsComstock power plant out of service for maintenance whendemand is expected to be low. After shutdown, performingmaintenance and getting the plant back on line takes two weeks. The utility has enough other generating capacity tosatisfy 1,550 megawatts (MW) of demand while Comstockis out of service. Table 8.5 shows weekly peak demands(in MW) for the past several autumns. When next in year 6should the Comstock plant be scheduled for maintenance?