OPERATION MANAGEMENT
2nd Edition
ISBN: 9781260242423
Author: CACHON
Publisher: MCG
expand_more
expand_more
format_list_bulleted
Concept explainers
Textbook Question
Chapter 15, Problem 4PA
A police station had to deploy police officers for emergencies multiple times the last four evenings. The numbers of emergencies for Monday, Tuesday, Wednesday, and Thursday were 7, 4, 8, and 11, respectively. What would be the station’s forecast for Friday using an exponential smoothing
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
A police station had to deploy a police officer for an emergency multiple times in the last four evenings. The table
below shows the number of emergencies each evening.
Weekday
Number of calls each day
Monday
5
Tuesday
Wednesday
Thursday
10
What would be their forecast for Friday using a naïve forecasting approach?
Forecast for Friday
calls
A security company had to deploy guards for emergencies multiple times in the last four evenings. The numbers of
emergencies for Monday, Tuesday, Wednesday, and Thursday were 7, 4, 8, and 11, respectively. What would be the
security company's forecast for the number of emergencies on Friday using an exponential smoothing forecasting
approach? (Use \alpha= 0.2 and a forecast for Monday of 10 emergencies)
A restaurant wants to forecast its weekly sales. Historical data (in dollars) for 15 weeks are shown in this Excel file (also shown in Problem 6 on page 243 in the textbook).
Answer the following questions related to this information:
Provide insight about the time series. What are the trends and stability of the data?
What is the forecast for Week 16, using a two-period moving average? (use cell B6 for number of periods)
What is the forecast for Week 16, using a three-period moving average? (use cell B6 for number of periods)
What is the MSE for the two- and three-period moving average models? Compare the results.
Find the best number of periods for the moving average model based on MSE.
Chapter 15 Solutions
OPERATION MANAGEMENT
Ch. 15 - When creating a time seriesbased forecast for the...Ch. 15 - Prob. 2CQCh. 15 - Prob. 3CQCh. 15 - Prob. 4CQCh. 15 - Prob. 5CQCh. 15 - Prob. 6CQCh. 15 - Prob. 7CQCh. 15 - Prob. 8CQCh. 15 - Using the moving average forecast, is it possible...Ch. 15 - Prob. 10CQ
Ch. 15 - Prob. 11CQCh. 15 - Prob. 12CQCh. 15 - Prob. 13CQCh. 15 - Deseasonalizing old demand data is the process of...Ch. 15 - Prob. 15CQCh. 15 - Prob. 1PACh. 15 - Prob. 2PACh. 15 - Prob. 3PACh. 15 - A police station had to deploy police officers for...Ch. 15 - MyApp is a small but growing startup that sees...Ch. 15 - Prob. 6PACh. 15 - Prob. 7PACh. 15 - Prob. 1CCh. 15 - CASE INTERNATIONAL ARRIVALS The U.S. Department of...Ch. 15 - Prob. 3C
Additional Business Textbook Solutions
Find more solutions based on key concepts
There is a huge demand in the United States and elsewhere for affordable women’s clothing. Low-cost clothing re...
Operations Management
There is a huge demand in the United States and elsewhere for affordable women’s clothing. Low-cost clothing re...
Loose-leaf for Operations Management (The Mcgraw-hill Series in Operations and Decision Sciences)
What are the three major business functions, and how are they related to one another? Give specific examples.
Operations Management, Binder Ready Version: An Integrated Approach
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
What is precedent, and how does it affect common law?
Business in Action (8th Edition)
What is precedent, and how does it affect common law?
Business in Action
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_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_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_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_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_forwardThe 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_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_forwardProfessor Z needs to allocate time among several tasks next week to include time for students' appointments. Thus, he needs to forecast the number of students who will seek appointments. He has gathered the following data: Week Number of students6 Weeks ago 515 Weeks ago 794 Weeks ago 833 Weeks ago 892 Weeks ago 71Last Week 93 What is this week's forecast using exponential smoothing with alpha = 0.3 , if the forecast for two weeks ago was 77 ? a. 75.2 b. 78.8 c. 69.86 d. 80.54arrow_forwardComplete the forecasting worksheets for: Naïve Average Moving Average Weighted Moving Average using the weights of .8, .15, and .05 with .8 being the most current, then .15, then .05 ExponA using and alpha level of .75 ExponB will automatically be .25 when A is .75 Exponential Solver What is the best alpha level as determined by the Exponential Solver? Which is the best forecasting option for MAE? What is the MAE? Which is the best forecasting option for MAPE? What is the MAPE? Period Sales 1 115 2 118 3 128 4 122 5 135 6 128 7 135 8 132 9 132 10 135arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,MarketingMarketingISBN:9780357033791Author:Pride, William MPublisher:South Western Educational PublishingContemporary MarketingMarketingISBN:9780357033777Author:Louis E. Boone, David L. KurtzPublisher:Cengage Learning
Practical Management Science
Operations Management
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:Cengage,
Marketing
Marketing
ISBN:9780357033791
Author:Pride, William M
Publisher:South Western Educational Publishing
Contemporary Marketing
Marketing
ISBN:9780357033777
Author:Louis E. Boone, David L. Kurtz
Publisher:Cengage Learning
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