8 Weekly sales of copy paper at Cubicle Suppliers are provided in the table below. Compute a three-period moving average and a four-period moving average for weeks 5, 6, and 7. Compute the MAD for both forecasting methods. Which model is more accurate? Forecast week 8 with the more accurate method. Week Sales (cases) 1 17 2 21 3 27 4 31 5 19 6 17 7 21

8 Weekly sales of copy paper at Cubicle Suppliers are provided in the table below. Compute a three-period moving average and a four-period moving average for weeks 5, 6, and 7. Compute the MAD for both forecasting methods. Which model is more accurate? Forecast week 8 with the more accurate method. Week Sales (cases) 1 17 2 21 3 27 4 31 5 19 6 17 7 21

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 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_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 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_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?
Give typed answer Question: Use an exponential smoothing model with a =.4 to forecast issues remediated for periods 6-10. (Assume a beginning forecast of 320 for period 5). 1. Forecast Period 6 (August) : ? 2. Forecast Period 7 (September) : ? 3. Forecast Period 8 (October) : ? 4. Forecast Period 9 (November) : ? 5. Forecast Period 10 (December) : ?
14 Community General Hospital finds itself treating many bicycle accident victims. Data from the last seven 24-hour periods is shown below: Day Bicycle Victims 1 8 2 14 3 8 4 14 5 18 6 15 With an alpha value of 0.31 and a starting forecast in day 3 equal to the 21 , what is the exponentially smoothed forecast for day 4? (Round to two decimal places) 15 What is the exponentially smoothed forecast for day 5? (Round to two decimal places) 16
Forecast sales for the 11th period. For leveling, use exponential smoothing 0.20 and moving average 3 for averaging; and linear and exponential functions for trend data. Assume an initial exponential forecast of 600 units in period 2 if you decide to use it (i.e., no forecast for period 1). Period 1 2 3 4 5 6 7 8 9 10 Sales 648 590 631 769 745 856 300 962 990 1100
The number of fishing rods selling each day is given below. Perform analyses of the time series to determine which model should be used for forecasting. 3 day moving average analysis 4 day moving average analysis 3 day weighted moving average analysis with weights W1=0.2, W2=0.3 and W3=0.5 with W1 on the oldest data. Exponential smoothing analysis with A=0.3 Which model provides a better fit of the data? Forecast day 13 sales of fishing rods using the model chosen in part (e) Day Rods Sold 1 60 2 70 3 110 4 80 5 70 6 85 7 115 8 105 9 65 10 75 11 95 12 85 Please read the relevant article, found in the VLE, before answering the question. Discuss the process and findings of the study of the article. Suggest a possible study that could be done at your current or past job that could use a similar methodology and analysis.
Use simple exponential smoothing with a=0.6 to forecast chargers sales for February through May. Assume that the forecast for January was 24 chargers. *** Month January Charger Sales 42 February 33 March 28 April 59 May ? a) What will be the forecast for May? b) Calculate the MSE.
12-1. The Hartley-Davis motorcycle dealer in the Minneapolis- St. Paul area wants to be able to forecast accurately the de- mand for the Roadhog Super motorcycle during the next month. From sales records, the dealer has accumulated the data in the following table for the past year. Month January February March April Мay June Motorcycle Sales 7 10 8 7 12 July August September 10 11 12 October 10 November December 14 16 a Compute a three-month moving average forecast of demand for April through January (of the next year). b. Compore a five-month moving average forecast for June drough January. c. Compare the two forecasts computed in parts (a) and (b) using MAD. Which one should the dealer use for January of dhe next year?
The manager of a popular tourist resort wants to use the manual trend projection forecasting technique and exponential smoothing without trend to forecast room occupancy at the resort for the next 4 years. Using a numerical example, demonstrate how these techniques can be used to do the forecast. REQUIREMENT- USE EXPONENTIAL SMOOTHING(WITHOUT TREND) ONLY