1. The operations manager of a musical instrument distributor feels that demand for bass drums may be related to the number of television appearances by the popular rock group Green Shades during the preceding month. The manager has collected the data shown in the following table: a). b). Demand for Bass Drums 3 6 7 5 10 8 Green Shades TV Appearances 3 4 7 6 8 5 Use the least squares regression method to derive a forecasting equation. What is your estimate for bass drum sales if the Green Shades performed on TV nine times last month?

1. The operations manager of a musical instrument distributor feels that demand for bass drums may be related to the number of television appearances by the popular rock group Green Shades during the preceding month. The manager has collected the data shown in the following table: a). b). Demand for Bass Drums 3 6 7 5 10 8 Green Shades TV Appearances 3 4 7 6 8 5 Use the least squares regression method to derive a forecasting equation. What is your estimate for bass drum sales if the Green Shades performed on TV nine times last month?

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.3: Simple Regression Models

Problem 2P: The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a...

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