Operations Management
13th Edition
ISBN: 9781259667473
Author: William J Stevenson
Publisher: McGraw-Hill Education
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Textbook Question
Chapter 3, Problem 12P
The following equation summarizes the trend portion of quarterly sales of condominiums over a long cycle. Sales also exhibit seasonal variations. Using the information given, prepare a
Ft = 40–6.5t + 2t2
Ft = Unit Sales
t = 0 at, the first quarter of last year
| Quarter | Relative |
| 1 | 1.1 |
| 2 | 1.0 |
| 3 | .6 |
| 4 | 1.3 |
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
The following equation summarizes the trend portion of quarterly sales of condominiums over a long cycle. Sales also exhibit seasonal variations. Ft = 51 − 4.1t + 3.1t 2 whereFt = Unit sales t = 0 at the first quarter of last year
Quarter
Relative
1
0.95
2
0.95
3
0.45
4
1.65
Click here for the Excel Data File
Using the information given, prepare a forecast of sales for each quarter of next year (not this year), and the first quarter of the year following that. (Round intermediate calculations and final answers to 2 decimal places.)
The following equation summarizes the trend portion of quarterly sales of condominiums over a long cycle. Sales also exhibit seasonal variations. Using the information given, prepare a forecast of sales for each quarter of next year (not this year), and the first quarter of the year following that.Ft = 40 – 6.5t + 2t2whereFt = UnitSales t = 0 at, the first quarter of last yearQuarter Relative1 1.12 1.03 .64 1.3
The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows:
YEAR
CASES OFMERLOT WINE
2005
321
2006
407
2007
449
2008
507
2009
409
2010
551
2011
461
2012
427
Using an exponential smoothing model with an alpha value of 0.30, estimate the smoothed value calculated as of the end of 2012. Use the average demand for 2005 through 2007 as your initial forecast for 2008, and then smooth the forecast forward to 2012.
Chapter 3 Solutions
Operations Management
Ch. 3.15 - Prob. 1.1RQCh. 3.15 - Prob. 1.2RQCh. 3.15 - Prob. 1.3RQCh. 3 - What are the main advantage that quantitative...Ch. 3 - What are some of the consequences of poor...Ch. 3 - List the specific weaknesses of each of these...Ch. 3 - Forecasts are generally wrong a. Why are forecasts...Ch. 3 - What is the purpose of establishing control limits...Ch. 3 - What factors would you consider in deciding...Ch. 3 - Contrast the use of MAD and MSE in evaluating...
Ch. 3 - What advantages as a forecasting tool does...Ch. 3 - How does the number of periods in a moving average...Ch. 3 - What factors enter into the choice of a value for...Ch. 3 - Prob. 11DRQCh. 3 - Explain how using a centered moving average with a...Ch. 3 - Contrast the terms sales and demand.Ch. 3 - Contrast the reactive and proactive approaches to...Ch. 3 - Explain how flexibility in production systems...Ch. 3 - How is forecasting in the context of a supply...Ch. 3 - Which type of forecasting approach, qualitative or...Ch. 3 - Prob. 18DRQCh. 3 - Choose the type of forecasting technique (survey,...Ch. 3 - Explain the trade-off between responsiveness and...Ch. 3 - Who needs to be involved in preparing forecasts?Ch. 3 - How has technology had an impact on forecasting?Ch. 3 - It has been said that forecasting using...Ch. 3 - What capability would an organization have to have...Ch. 3 - When a new business is started, or a patent idea...Ch. 3 - Discuss how you would manage a poor forecast.Ch. 3 - Omar has beard from some of his customers that...Ch. 3 - Give three examples of unethical conduct involving...Ch. 3 - A commercial baker, has recorded sales (in dozens)...Ch. 3 - National Scan, Inc., sells radio frequency...Ch. 3 - A dry cleaner uses exponential smoothing to...Ch. 3 - An electrical contractors records during the last...Ch. 3 - A cosmetics manufacturer s marketing department...Ch. 3 - Prob. 6PCh. 3 - Freight car loadings ova a 12-year period at a...Ch. 3 - Air travel on Mountain Airline for the past 18...Ch. 3 - a. Obtain the linear trend equation for the...Ch. 3 - After plotting demand for four periods, an...Ch. 3 - A manager of a store that sells and installs spas...Ch. 3 - The following equation summarizes the trend...Ch. 3 - Compute seasonal relatives for this data the SA...Ch. 3 - A tourist center is open on weekends (Friday,...Ch. 3 - The manager of a fashionable restaurant open...Ch. 3 - Obtain estimates of daily relatives for the number...Ch. 3 - A pharmacist has been monitoring sales of 2...Ch. 3 - New car sales for a dealer in Cook County,...Ch. 3 - The following table shows a tool and die companys...Ch. 3 - An analyst must decide between two different...Ch. 3 - Two different forecasting techniques (F1 and F2)...Ch. 3 - Two independent methods of forecasting based on...Ch. 3 - Long-Life Insurance has developed a linear model...Ch. 3 - Timely Transport provides local delivery service...Ch. 3 - The manager of a seafood restaurant was asked to...Ch. 3 - The following data were collected during a study...Ch. 3 - Lovely Lawns Inc., intends to use sales of lawn...Ch. 3 - The manager of a travel agency has been using a...Ch. 3 - Refer to the data in problem 22 a. Compute a...Ch. 3 - The classified department of a monthly magazine...Ch. 3 - A textbook publishing company has compiled data on...Ch. 3 - A manager has just receded an valuation from an...Ch. 3 - A manager uses this equation to predict demand for...Ch. 3 - A manager uses a trend equation plus quarterly...Ch. 3 - ML MANUFACTURING ML Manufacturing makes various...Ch. 3 - ML MANUFACTURING ML Manufacturing makes various...Ch. 3 - HIGHLINE FINANCIAL SERVICES, LTD. Highline...
Additional Business Textbook Solutions
Find more solutions based on key concepts
2. Identify four people who have contributed to the theory and techniques of operations management.
Operations Management
What is precedent, and how does it affect common law?
Business in Action (8th Edition)
2. Identify four people who have contributed to the theory and techniques of operations management.
Operations Management: Sustainability and Supply Chain Management (12th Edition)
Feeding America Each year, the Feeding America network helps provide food to more than 46 million people facing...
Operations and Supply Chain Management 9th edition
Mary Williams, owner of Williams Products, is evaluating whether to introduce a new product line. After thinkin...
Operations Management: Processes and Supply Chains (11th Edition)
The Big Black Bird Company (BBBC) has a large order for special plastic-lined military uniforms to be used in a...
Operations Management: Processes and Supply Chains (12th Edition) (What's New in Operations Management)
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_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.arrow_forward
- 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?arrow_forwardThe 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?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_forwardDo 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 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_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_forwardThe management of a technology company is trying to determine the variable that best explains the variation of employee salaries using a sample of 52 full-time employees; see the file P13_08.xlsx. Estimate simple linear regression equations to identify which of the following has the strongest linear relationship with annual salary: the employees gender, age, number of years of relevant work experience prior to employment at the company, number of years of employment at the company, or number of years of post secondary education. Provide support for your conclusion.arrow_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