↑As you can see in the following table, demand for heart transplant surgery at Washington General Hospital has increased steadily in the past few years1Year2 3 4 5Heart Transplants 46.0 52.0 52.0 57.0 60.0The director of medical services predicted 6 years ago that demand in year 1 would be 42.0 surgeriesa) Using exponential smoothing with a of 0.60 and the given forecast for year 1, the forecasts for years 2 through 6 are (round your responses to one decimal place)235 6YearForecast142.04

A common forecasting technique is exponential smoothing, which uses the previous measurements of a…

Answered: As you can see in the following table,…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section: Chapter Questions

Problem 42P: The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars)...

See similar textbooks

Similar questions

Under what conditions might a firm use multiple forecasting methods?
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?
The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.
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?
The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?
The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?
- Sales of tablet computers at Ted Glickman's electronics store in Washington, D.C., over the past 10 weeks are shown in the table below: 6 10 Week 1 Demand 20 2 3 23 27 4 5 37 26 7 8 9 30 35 22 24 29 a) The forecast for weeks 2 through 10 using exponential smoothing with a = 0.55 and a week 1 initial forecast of 20.0 are (round your responses to two decimal places): Week 1 Demand 20 Forecast 20.0 2 3 23 27 4 37 5 26 6 30 7 35 8 22 9 24 10 29
12-1. The Hartley-Davis motorcycle dealer in the Minneapolis- St. Paul area wants to be able to forecast accurately the de- mand for the Roadhog Super motorcycle during the next month. From sales records, the dealer has accumulated the data in the following table for the past year. Month January February March April Мay June Motorcycle Sales 7 10 8 7 12 July August September 10 11 12 October 10 November December 14 16 a Compute a three-month moving average forecast of demand for April through January (of the next year). b. Compore a five-month moving average forecast for June drough January. c. Compare the two forecasts computed in parts (a) and (b) using MAD. Which one should the dealer use for January of dhe next year?
Clinic administrator Marc Schniederjans wants you to forecastpatient demand at the clinic for week 7 by using this data. You decide to use a weighted moving average method to find this fore-cast. Your method uses four actual demand levels, with weights of 0.333 on the present period, 0.25 one period ago, 0.25 two peri-ods ago, and 0.167 three periods ago. a) What is the value of your forecast? PXb) If instead the weights were 20, 15, 15, and 10, respectively, howwould the forecast change? Explain why. c) What if the weights were 0.40, 0.30, 0.20, and 0.10, respec-tively? Now what is the forecast for week 7?
Make a 15-year simple linear regression forecast. Example: Railroad Products Co. RPC Sales Car Loadings Year ($millions) (millions) 1 9.5 120 2 11.0 135 3 12.0 130 4 12.5 150 5 14.0 170 6 16.0 190 7 18.0 220
The demand (in number of units) for Apple iPad over the past 6 months at BestBuy is summarized below. Month Nov 2019 Dec 2019 Demand 45 48 Jan 2020 50 Feb 2020 Mar 2020 Apr 2020 42 46 51 Consider the following three forecasting methods: • Two-month weighted moving average, with weights 6 and 2 (more weight assigned to more recent data) Exponential smoothing with a = 0.7. Let the initial forecast for Nov 2019 be 46. • A trend line projection in the form ŷ = a+bx . To simplify computations, transform the value of x (time) to simpler numbers – designate Nov 2019 as x=1, Dec 2019 as x= 2, etc. (a ) For each of the above methods, forecast the demand of Apple iPad for May 2020. (b) Consider only the two-month weighted moving average method, compute the MAD measure and the MSE measure using the data from Jan 2020. (c) Use the trend line to forecast the demand of Apple iPad for Dec 2020. Give your opinion regarding the reliability of the forecast.
To have a stable forecasting tool when using the simple moving average method, what value of N (the number of periods) should a firm choose among the following choices? a. 3b. 2c. 8d. 6

SEE MORE QUESTIONS

Recommended textbooks for you

Practical Management Science

Operations Management

ISBN:

9781337406659

Author:

WINSTON, Wayne L.

Publisher:

Cengage,

Contemporary Marketing

Marketing

ISBN:

9780357033777

Author:

Louis E. Boone, David L. Kurtz

Publisher:

Cengage Learning

Marketing

ISBN:

9780357033791

Author:

Pride, William M

Publisher:

South Western Educational Publishing

Practical Management Science

Operations Management

ISBN:

9781337406659

Author:

WINSTON, Wayne L.

Publisher:

Cengage,

Contemporary Marketing

Marketing

ISBN:

9780357033777

Author:

Louis E. Boone, David L. Kurtz

Publisher:

Cengage Learning

Marketing

ISBN:

9780357033791

Author:

Pride, William M

Publisher:

South Western Educational Publishing

MARKETING 2018

Marketing

ISBN:

9780357033753

Author:

Pride

Publisher:

CENGAGE L

SEE MORE TEXTBOOKS