Moving average is used to forecast room demand. Generatea forecast for June using MA =2 and MA = 4. What are thefrom this approach? Which is closer to the actualforecastsfor June?MonthJanuaryFebruaryMarchAprilMayJuneActualDemand120012101150114011301160Forecast1220

To find: The forecast from this approach, and which is closer to the actual for June. Given: The…

Answered: Moving average is used to forecast room…

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 28P: The file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. a. Is seasonality present...

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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.
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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?
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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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st Info Period 1 2 3 4 5 6 7 8 9 10 K Develop two exponential smoothing forecasts for periods 2 through 11. For the first forecast, use a = 0.3. For the second, use α = 0.7. Assume that your forecast for period 1 was 205. Click the icon to view the time series data. Find the exponential smoothing forecast for each period when a = 0.3 (enter your responses rounded to one decimal place). Demand 222 249 222 228 235 155 161 153 163 152 X Period 1 2 Demand 222 249 Forecast (α = 0.3) 205
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Moving average is used to forecast room demand. Generate. a forecast for June using MA =2 and MA = 4. What are the forecasts from this approach? Which is closer to the actual for June? Month January February March April May June Actual Demand 1200 1210 1150 1140 1130 1160 Forecast 1220