bodyde:A manager wants to choose one of two forecasting alternatives: moving average and exponentialsmoothing. Each alternative was tested using historical data. The resulting forecast errors for thetwo are shown in the table.Period (t)Forecasting Errors using Moving AverageForecasting Errors using ExponentialSmoothing13423-22-3 342-1523(a) Calculate MAD for Moving Average Method and Exponential Smoothing Method(b) Calculate MSE for Moving Average Method and Exponential Smoothing Method645(c) Based on Part (a) and Part (b), which forecasting method (Moving Average or ExponentialSmoothing) should be used in this problem? Please explain your reasons.

A manager wants to choose one of two forecasting alternatives: moving average and exponential smoothing. Each alternative was tested using historical data. The resulting forecast errors for the two are shown in the table. Period (t) Forecasting Errors using Moving Average Forecasting Errors using Exponential Smoothing 1 نها 3 4 2 -2 نہ -3 323 4 2 -1 523 (a) Calculate MAD for Moving Average Method and Exponential Smoothing Method (b) Calculate MSE for Moving Average Method and Exponential Smoothing Method 6 4 5

A manager wants to choose one of two forecasting alternatives: moving average and exponential smoothing. Each alternative was tested using historical data. The resulting forecast errors for the two are shown in the table. Period (t) Forecasting Errors using Moving Average Forecasting Errors using Exponential Smoothing 1 نها 3 4 2 -2 نہ -3 323 4 2 -1 523 (a) Calculate MAD for Moving Average Method and Exponential Smoothing Method (b) Calculate MSE for Moving Average Method and Exponential Smoothing Method 6 4 5

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...

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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.
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 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_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_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_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 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_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?
At the ABC Floral Shop, an argument developed between two of the owners, Bob and Henry, over the accuracy of forecasting methods. Bob argued that exponential smoothing with α = .1 would be the best method. Henry argued that the shop would get a better forecast with α = .3.a. Using F1 = 100 and the data from problem 3, which of the two managers is right?b. Graph the two forecasts and the original data using Excel. What does the graph reveal?c. Maybe forecast accuracy could be improved. Try additional values of α = .2, .4, and .5 to see if better accuracy is achieved.
Complete the forecasting worksheets for:NaïveAverageMoving AverageWeighted Moving Average using the weights of .8, .15, and .05 with .8 being the most current, then .15, then .05ExponA use an alpha level of .75ExponB use an alpha level of .25Exponential SolverWhat is the best alpha level as determined by the Exponential Solver?Which is the best forecasting option for MAE? What is the MAE?Which is the best forecasting option for MAPE? What is the MAPE? Period Sales This is the data for the forecasting template1 1152 1183 1284 1225 1356 1287 1358 1329 13210 135
4 .Substitute for Problem # 4 on in attachment)-Calculate the MAD,revised MAD and the Revised Forecast for months 1-6 for the following three groups,where the Forecast stands for Forecast Demand.Has your forecast improved ? Tell me how would you go about improving the revised forecast( for each of the three groups)without actually doing so? Estate Planning Group Auditing and Accounting Group Business Consulting Group Month Actual Demand Forecast Actual Demand Forecast Actual Demand Forecast 1 100 125 270 230 140 135 2 90 125 240 230 130 135 3 110 125 280 230 160 135 4 115 125 260 230 180 135 5 130 125 300 230 200 135 6 115 125 220 230 190 135