a) Using a 2-year moving average, the forecast for year 6= 3750 miles (round your response to the nearest whole number) b) If a 2-year moving average is used to make the forecast, the MAD based on this = 116.7 miles (round your response to one decimal place) (Hint You will have only 3 years of matched data) c) The forecast for year 6 using a weighted 2-year moving average with weights of 0.35 and 0.65 (the weight of 0.65 is for the most recent period) = 3750 miles (round your response to the nearest whole number). The MAD for the forecast developed using a weighted 2-year moving average with weights of 0.35 and 0.65= miles (round your response to one decimal place) (Hint You will have only 3 years of matched data.)

a) Using a 2-year moving average, the forecast for year 6= 3750 miles (round your response to the nearest whole number) b) If a 2-year moving average is used to make the forecast, the MAD based on this = 116.7 miles (round your response to one decimal place) (Hint You will have only 3 years of matched data) c) The forecast for year 6 using a weighted 2-year moving average with weights of 0.35 and 0.65 (the weight of 0.65 is for the most recent period) = 3750 miles (round your response to the nearest whole number). The MAD for the forecast developed using a weighted 2-year moving average with weights of 0.35 and 0.65= miles (round your response to one decimal place) (Hint You will have only 3 years of matched data.)

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.7: Exponential Smoothing Models

Problem 26P: The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel...

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_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?
The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?
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?
The file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?
The Carbondale Hospital is considering the purchase of a new ambulance. The decision will rest partly on the anticipated mileage to be driven next year. The miles driven during the past 5 years are as follows: Year 1 2 3 4 5Mileage 3,000 4,050 3,450 3,800 3,800 a) Using a 2-year moving average, the forecast for year 6 = 38003800 miles (round your response to the nearest whole number). a) Using a 2-year moving average, the forecast for year 6 = 3800 miles (round your response to the nearest whole number). b) If a 2-year moving average is used to make the forecast, the MAD based on this = 100.0 miles (round your response to one decimal place). (Hint: You will have only 3 years of matched data.) c) The forecast for year 6 using a weighted 2-year moving average with weights of 0.45 and 0.55 (the weight of 0.55 is for the most recent period) = ? miles (round your response to the nearest whole number).
The Grand Bakery produces 60 special sourdough rolls every day. Any rolls that are not sold each day are given to the employees. They have collected sales data from the past week: Day Rolls sold 1 50 2 50 3 48 4 60 5 53 6 60 What is the value of F6 if they use a 3-day weighted moving average with W1 = 0.6, W2 = 0.2, and W3 = 0.2? Using the data from above, calculate the forecast for period 7 using a four-period moving average:
The Carbondale Hospital is considering the purchase of a new ambulance. The decision will rest partly on the anticipated mileage to be driven next year. The miles driven during the past 5 years are as follows: Year 1 2 3 4 5 Mileage 3,100 4,000 3,500 3,800 3,700 a) Using a 2-year moving average, the forecast for year 6 =______miles (round your response to the nearest whole number). b) If a 2-year moving average is used to make the forecast, the MAD based on this =____miles (round your response to onedecimal place). (Hint: You will have only 3 years of matched data.) c) The forecast for year 6 using a weighted 2-year moving average with weights of 0.45 and 0.55 (the weight of 0.55 is for the most recent period) =________miles (round your response to the nearest whole number). The MAD for the forecast developed using a weighted 2-year moving average with weights of 0.45 and 0.55=_____…
Consider the following time series data. Week 1 2 3 4 5 6 Value 18 12 15 11 18 13 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) Mean absolute error If required, round your answer to one decimal place. (b) Mean squared error If required, round your answer to one decimal place. (c) Mean absolute percentage error If required, round your intermediate calculations and final answer to two decimal places. (d) What is the forecast for week 7?