Please only do this typewritten, so everything is visible. I have a hard time reading handwritten solutions. i hope you understand. thank you. i will upvoteSKIP THIS IF YOU ALREADY DID THIS OR GET DOWNVOTE Period1234567Actual4241394345F??22. Using the same table above, compute the weighted moving averageforecast for demand for four latest period. With data using a weight of .40for the most recent, .30 for the next recent, .20 the next, and .10 for theoldest. Assume actual demand for period 6 is 44, what is the forecast forperiod 7?

Forecasting is a technique used to predict future outcomes on the basis of past data. In businesses…

2. Using the same table above, compute the weighted moving average forecast for demand for four latest period. With data using a weight of .40 for the most recent, .30 for the next recent, .20 the next, and .10 for the oldest. Assume actual demand for period 6 is 44, what is the forecast for period 7?

2. Using the same table above, compute the weighted moving average forecast for demand for four latest period. With data using a weight of .40 for the most recent, .30 for the next recent, .20 the next, and .10 for the oldest. Assume actual demand for period 6 is 44, what is the forecast for period 7?

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...

See similar textbooks

Similar questions

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 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 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_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 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?
Clinic administrator Marc Schniederjans wants you to forecastpatient demand at the clinic for week 7 by using this data. You decide to use a weighted moving average method to find this fore-cast. Your method uses four actual demand levels, with weights of 0.333 on the present period, 0.25 one period ago, 0.25 two peri-ods ago, and 0.167 three periods ago. a) What is the value of your forecast? PXb) If instead the weights were 20, 15, 15, and 10, respectively, howwould the forecast change? Explain why. c) What if the weights were 0.40, 0.30, 0.20, and 0.10, respec-tively? Now what is the forecast for week 7?
Compute the one-step-ahead three-month and six-month moving-average forecastsfor July through December. What effect does increasing N from 3 to 6 have on theforecasts?
*** Can you please demonstrate how to do parts d, e, f? Given: Year Demand 1 7 2 9 3 5 4 9 5 Predict the value for Year 5: 2 year moving average What is MSE for 2 year moving average? 2 year moving average using 0.6 (weight for the oldest period) and 0.4(weight for most recent period Exponential smoothing, =0.2 and forecast for Year 1 = 5 Linear trend Which forecast method has the least amount of error using MAD? What is the coefficient?
Herman Hahn is attempting to set up an integrated forecasting and inventory controlsystem for his hardware store, Hahn’s Hardware. When Herman indicates that outdoorlights are a seasonal item on the computer, he is prompted by the program to input theseasonal factors by quarter.Unfortunately, Herman has not kept any historical data, but he estimates that firstquarter demand for the lights is about 30 percent below average, the second-quarterdemand about 20 percent below average, third-quarter demand about average, andfourth-quarter demand about 50 percent above average. What should he input for theseasonal factors?
You discovered that the forecasting error falls beyond the acceptable ranges in the past three years. Make a reliable forecast for the demand on your product/service using at least 10 periods of your historical data to forecast the demand for the coming 5 periods. Then compute the MAD for these 5 periods . Period Actual (A) Forecast (F) (A-F) Error 1 107 110 -3 2 125 121 4 3 115 112 3 4 118 120 -2 5 108 109 1 6 118 120 -2 7 108 109 1 8 115 112 -3 9 140 137 -3 10 106 102 -4