Principles Of Operations Management
11th Edition
ISBN: 9780135173930
Author: RENDER, Barry, HEIZER, Jay, Munson, Chuck
Publisher: Pearson,
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Question
Chapter 4, Problem 38P
a)
Summary Introduction
To compute: The demand for vacuum cleaners using a three-period moving average.
b)
Summary Introduction
To compute: The demand for vacuum cleaners using a three-period weighted moving average.
c)
Summary Introduction
To determine: The better forecast using MAD.
d)
Summary Introduction
To determine: The factors to be considered in
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
Sales of industrial vacuum cleaners at Larry Armstrong Supply Co. over the past I 3 months are shown below: a) Using a moving average with three periods, determine the demand for vacuum cleaners for next February.b) Using a weighted moving average with three periods, determine the demand for vacuum cleaners for February. Use 3, 2, and l for the weights of the most recent, second most recent, and third most recent periods, respectively. For example, if you were forecasting the demand for February, November would have a weight of l, December would have a weight of 2, and January would have a weight of3.c) Using MAD, determine which is the better forecast.d) What other factors might Armstrong consider in forecasting sales?
4
Use simple exponential smoothing with a -0.8
to forecast electric scooter sales at Guelph-
Humber Inc. for July. Assume that the
forecast for May was for 45 electric scooters.
Round your answer to 1 decimal
Electric Scooter Sales
Month
May 42
June 47
July 45
August 40
Weekly demand for medical masks for the
last five weeks at Chopper Drug Store has
been as follows: 92, 96, 100, 100 and 102
(listed from the oldest to most recent).
Suppose a naive forecast was used to
forecast demand. What would the MAD be for
this situation?
Enrollment in a particular Yoga class at
Guelph Fitness Centre for the last five
months has been 80, 86, 88, 88 and 90(listed
from the oldest to most recent). Suppose a
two-month mov
average was used to
forecast enrollment. What would the MSE be
for this situation?
Chapter 4 Solutions
Principles Of Operations Management
Ch. 4 - Ethical Dilemma We live in a society obsessed with...Ch. 4 - What is a qualitative forecasting model, and when...Ch. 4 - Identify and briefly describe the two general...Ch. 4 - Identify the three forecasting time horizons....Ch. 4 - Briefly describe the steps that are used to...Ch. 4 - A skeptical manager asks what medium-range...Ch. 4 - Explain why such forecasting devices as moving...Ch. 4 - What is the basic difference between a weighted...Ch. 4 - What three methods are used to determine the...Ch. 4 - Research and briefly describe the Delphi...
Ch. 4 - What is the primary difference between a...Ch. 4 - Define time series.Ch. 4 - What effect does the value of the smoothing...Ch. 4 - Explain the value of seasonal indices in...Ch. 4 - Prob. 14DQCh. 4 - In your own words, explain adaptive forecasting.Ch. 4 - Prob. 16DQCh. 4 - Explain, in your own words, the meaning of the...Ch. 4 - Prob. 18DQCh. 4 - Give examples of industries that are affected by...Ch. 4 - Prob. 20DQCh. 4 - Prob. 21DQCh. 4 - CEO John Goodale, at Southern Illinois Power and...Ch. 4 - The following gives the number of pints of type B...Ch. 4 - a) Plot the above data on a graph. Do you observe...Ch. 4 - Refer to Problem 4.2. Develop a forecast for years...Ch. 4 - A check-processing center uses exponential...Ch. 4 - The Carbondale Hospital is considering the...Ch. 4 - The monthly sales for Yazici Batteries, Inc., were...Ch. 4 - Prob. 7PCh. 4 - Daily high temperatures in St. Louis for the last...Ch. 4 - Lenovo uses the ZX-81 chip in some of its laptop...Ch. 4 - Data collected on the yearly registrations for a...Ch. 4 - Use exponential smoothing with a smoothing...Ch. 4 - Prob. 12PCh. 4 - At you can see in the following table, demand for...Ch. 4 - Prob. 14PCh. 4 - Refer to Solved Problem 4.1 on page 144. a) Use a...Ch. 4 - Prob. 16PCh. 4 - Prob. 17PCh. 4 - Prob. 18PCh. 4 - Income at the architectural firm Spraggins and...Ch. 4 - Resolve Problem 4.19 with = .1 and =.8. Using...Ch. 4 - Prob. 21PCh. 4 - Refer to Problem 4.21. Complete the trend-adjusted...Ch. 4 - Prob. 23PCh. 4 - The following gives the number of accidents that...Ch. 4 - In the past, Peter Kelles tire dealership in Baton...Ch. 4 - George Kyparisis owns a company that manufactures...Ch. 4 - Attendance at Orlandos newest Disneylike...Ch. 4 - Prob. 28PCh. 4 - The number of disk drives (in millions) made at a...Ch. 4 - Prob. 30PCh. 4 - Emergency calls to the 911 system of Durham, North...Ch. 4 - Using the 911 call data in Problem 4.31, forecast...Ch. 4 - Storrs Cycles has just started selling the new...Ch. 4 - Prob. 35PCh. 4 - Prob. 36PCh. 4 - Prob. 37PCh. 4 - Prob. 38PCh. 4 - Prob. 39PCh. 4 - Prob. 40PCh. 4 - Prob. 41PCh. 4 - Prob. 42PCh. 4 - Mark Gershon, owner of a musical instrument...Ch. 4 - Prob. 44PCh. 4 - Cafe Michigans manager, Gary Stark, suspects that...Ch. 4 - Prob. 46PCh. 4 - The number of auto accidents in Athens, Ohio, is...Ch. 4 - Rhonda Clark, a Slippery Rock, Pennsylvania, real...Ch. 4 - Accountants at the Tucson firm, Larry Youdelman,...Ch. 4 - Prob. 50PCh. 4 - Using the data in Problem 4.30, apply linear...Ch. 4 - Bus and subway ridership for the summer months in...Ch. 4 - Prob. 53PCh. 4 - Dave Fletcher, the general manager of North...Ch. 4 - Prob. 55PCh. 4 - Prob. 56PCh. 4 - Prob. 57PCh. 4 - Sales of tablet computers at Ted Glickmans...Ch. 4 - The following are monthly actual and forecast...Ch. 4 - Prob. 1CSCh. 4 - Prob. 2CSCh. 4 - Prob. 3CSCh. 4 - Prob. 1.1VCCh. 4 - Prob. 1.2VCCh. 4 - Using Perezs multiple-regression model, what would...Ch. 4 - Prob. 1.4VCCh. 4 - Prob. 2.1VCCh. 4 - Prob. 2.2VCCh. 4 - Prob. 2.3VCCh. 4 - Prob. 2.4VCCh. 4 - Prob. 2.5VC
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, operations-management and related others by exploring similar questions and additional content below.Similar questions
- Under what conditions might a firm use multiple forecasting methods?arrow_forwardThe 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?arrow_forwardThe 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?arrow_forward
- 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?arrow_forwardThe 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?arrow_forwardThe 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?arrow_forward
- 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?arrow_forwardSuppose that a regional express delivery service company wants to estimate the cost of shipping a package (Y) as a function of cargo type, where cargo type includes the following possibilities: fragile, semifragile, and durable. Costs for 15 randomly chosen packages of approximately the same weight and same distance shipped, but of different cargo types, are provided in the file P13_16.xlsx. a. Estimate a regression equation using the given sample data, and interpret the estimated regression coefficients. b. According to the estimated regression equation, which cargo type is the most costly to ship? Which cargo type is the least costly to ship? c. How well does the estimated equation fit the given sample data? How might the fit be improved? d. Given the estimated regression equation, predict the cost of shipping a package with semifragile cargo.arrow_forwardManagement of a home appliance store wants to understand the growth pattern of the monthly sales of a new technology device over the past two years. The managers have recorded the relevant data in the file P13_05.xlsx. Have the sales of this device been growing linearly over the past 24 months? By examining the results of a linear trend line, explain why or why not.arrow_forward
- Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.arrow_forwardThe number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows: YEAR CASES OF MERLOT WINE 1 270 2 356 3 398 4 456 5 358 6 500 7 410 8 376 Using an exponential smoothing model with an alpha value of 0.20, estimate the smoothed value calculated as of the end of year 8. Use the average demand for years 1 through 3 as your initial forecast for year 4, and then smooth the forecast forward to year 8. Note: Round your intermediate calculations and final answer to the nearest whole number.arrow_forwardAfter using your forecasting model for six months, you decide to test it using a tracking signal. Here are the forecast and actual demands for the six-month period: PERIOD FORECAST ACTUAL May 450 500 June 500 550 July 550 400 August 600 500 September 650 675 October 700 600 Find the tracking signal of each montharrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,
Contemporary MarketingMarketingISBN:9780357033777Author:Louis E. Boone, David L. KurtzPublisher:Cengage Learning
MarketingMarketingISBN:9780357033791Author:Pride, William MPublisher: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
Marketing
ISBN:9780357033791
Author:Pride, William M
Publisher:South Western Educational Publishing
Single Exponential Smoothing & Weighted Moving Average Time Series Forecasting; Author: Matt Macarty;https://www.youtube.com/watch?v=IjETktmL4Kg;License: Standard YouTube License, CC-BY
Introduction to Forecasting - with Examples; Author: Dr. Bharatendra Rai;https://www.youtube.com/watch?v=98K7AG32qv8;License: Standard Youtube License