Given the following data for demand at the XYZ Company, calculate the monthly forecast using a 4-month moving average. Calculate the Bias and the TS (tracking signal) . Period Demand Forecast Error MAD Bias TS 2-Oct 2020 850 　　　　　 2-Nov 2020 950 　　　　　 2-Dec 2020 900 　　　　　 2-Jan 2021 1000 　　　　　 2-Feb 2021 950 　　　　　 2-Mar 2021 1050 　　　　　 2-Apr 2021 850 2-May 2021 800 2-June 2021 900 2-July 2021 1000

Given the following data for demand at the XYZ Company, calculate the monthly forecast using a 4-month moving average. Calculate the Bias and the TS (tracking signal) . Period Demand Forecast Error MAD Bias TS 2-Oct 2020 850 　　　　　 2-Nov 2020 950 　　　　　 2-Dec 2020 900 　　　　　 2-Jan 2021 1000 　　　　　 2-Feb 2021 950 　　　　　 2-Mar 2021 1050 　　　　　 2-Apr 2021 850 2-May 2021 800 2-June 2021 900 2-July 2021 1000

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 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_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 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_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_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_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_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 following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 7 9 6 10 12 7 12 12 9 9 8 Part 2 Using exponential smoothing with α = 0.30 and a forecast for year 1 of 6.0, provide the forecast from periods 2 through 12 (round your responses to one decimal place). Part 3 Provide the forecast from periods 2 through 12 using the naive approach (enter your responses as whole numbers).
. Given the following data for demand at the XYZ Company, calculate the monthly forecast using a 4-month moving average. Calculate the Forecast, Error, MAD (mean absolute percentage error), Bias and the TS (tracking signal) . Period Demand Forecast Error MAD Bias TS 2-Oct 2020 850 　　　　　 2-Nov 2020 950 　　　　　 2-Dec 2020 900 　　　　　 2-Jan 2021 1000 　　　　　 2-Feb 2021 950 　　　　　 2-Mar 2021 1050 　　　　　 2-Apr 2021 850 2-May 2021 800 2-June 2021 900 2-July 2021 1000
National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below: Sales (1000 units) Forecast Observation Month Yt Ft 1 February 19 2 March 18 3 April 15 4 May 20 5 June 18 6 July 22 7 August 20 8 September ? Use Excel to plot the data and forecast September sales using the following methods: The naïve forecast A three-month moving average Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19 A 3-month weighted moving average, with weights 0.60, 0.3, and 0.1. With 0.6 applied to the most recent past.

SEE MORE QUESTIONS

Recommended textbooks for you

Practical Management Science

Operations Management

ISBN:

9781337406659

Author:

WINSTON, Wayne L.

Publisher:

Cengage,

Contemporary Marketing

Marketing

ISBN:

9780357033777

Author:

Louis E. Boone, David L. Kurtz

Publisher:

Cengage Learning

Marketing

ISBN:

9780357033791

Author:

Pride, William M

Publisher:

South Western Educational Publishing

Practical Management Science

Operations Management

ISBN:

9781337406659

Author:

WINSTON, Wayne L.

Publisher:

Cengage,

Contemporary Marketing

Marketing

ISBN:

9780357033777

Author:

Louis E. Boone, David L. Kurtz

Publisher:

Cengage Learning

Marketing

ISBN:

9780357033791

Author:

Pride, William M

Publisher:

South Western Educational Publishing

SEE MORE TEXTBOOKS

GET THE APP

About FAQ Academic Integrity Sitemap Document Sitemap

Contact Bartleby Contact Research (Essays)High School Textbooks Literature Guides Concept Explainers by Subject Essay Help Mobile App

GET THE APP

Privacy

Your CA Privacy Rights

Your NV Privacy Rights

About Ads

Manage My Data

bartleby, a Learneo, Inc. business

Period	Demand	Forecast	Error	MAD	Bias	TS
2-Oct 2020	850
2-Nov 2020	950
2-Dec 2020	900
2-Jan 2021	1000
2-Feb 2021	950
2-Mar 2021	1050
2-Apr 2021	850
2-May 2021	800
2-June 2021	900
2-July 2021	1000