A company wants to forecast demand using the weighted moving average. If the company uses three prior yearly sales values (i.e., the year 2014 = 155, the year 2015 = 140 and year 2016 = 170), and we want to weight the year 2014 at 30%, the year 2015 at 35% and year 2016 at 40%, which of the following is the weighted moving average forecast for the year 2017? 170 158 O 164 O 160

A company wants to forecast demand using the weighted moving average. If the company uses three prior yearly sales values (i.e., the year 2014 = 155, the year 2015 = 140 and year 2016 = 170), and we want to weight the year 2014 at 30%, the year 2015 at 35% and year 2016 at 40%, which of the following is the weighted moving average forecast for the year 2017? 170 158 O 164 O 160

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.6: Moving Averages Models

Problem 22P: The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six...

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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?
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?
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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.
Under what conditions might a firm use multiple forecasting methods?
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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?
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