Operations Management: Sustainability and Supply Chain Management (12th Edition)
12th Edition
ISBN: 9780134130422
Author: Jay Heizer, Barry Render, Chuck Munson
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Textbook Question
Chapter 4, Problem 1P
The following gives the number of pints of type B blood used at Woodlawn Hospital in the past 6 weeks:
| WEEK OF | PINTS USED |
| August 31 | 360 |
| September 7 | 389 |
| September 14 | 410 |
| September 21 | 381 |
| September 28 | 368 |
| October 5 | 374 |
- a.
Forecast the demand for the week of October 12 using a 3-week moving average. - b. Use a 3-week weighted moving average, with weights of .1, .3, and .6, using .6 for the most recent week. Forecast demand for the week of October 12.
- c. Compute the forecast for the week of October 12 using exponential smoothing with a forecast for August 31 of 360 and α =.2.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks:
Week Of
August 31
September 7
September 14
September 21
September 28
October 5
Pints Used
350
370
410
381
371
378
a) The forecasted demand for the week of October 12 using a 3-week moving average = 376.67 pints (round your
response to two decimal places).
b) Using a 3-week weighted moving average, with weights of 0.20, 0.35, and 0.45, using 0.45 for the most
recent week, the forecasted demand for the week of October 12 =
pints (round your response to two decimal
places and remember to use the weights in appropriate order the largest weight applies to most recent period and
smallest weight applies to oldest period.)
1. The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks:
Part 2
Week Of
Pints Used
August 31
350
September 7
372
September 14
412
September 21
381
September 28
366
October 5
378
Part 3
a) The forecasted demand for the week of October 12 using a 3-week
moving average
LOADING...
= _____________pints (round your response to two decimal places).
The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks:
Week Of
August 31
September 7
September 14
September 21
September 28
October 5
Pints Used
345
389
412
383
366
371
a) The forecasted demand for the week of October 12 using a 3-week moving average
decimal places).
pints (round your response to two
Chapter 4 Solutions
Operations Management: Sustainability and Supply Chain Management (12th Edition)
Ch. 4 - What is a qualitative foretasting 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 - Which forecasting technique can place the most...Ch. 4 - In your own words, explain adaptive forecasting.Ch. 4 - What is the purpose of a tracking signal?Ch. 4 - Explain, in your own words, the meaning of the...Ch. 4 - What is the difference between a dependent and an...Ch. 4 - Give examples of industries that are affected by...Ch. 4 - Give examples of industries in which demand...Ch. 4 - Prob. 21DQCh. 4 - Prob. 22DQCh. 4 - The following gives the number of pints of type B...Ch. 4 - 4.2 a. Plot the above data on a graph. Do you...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 - The actual demand for the patients at Omaha...Ch. 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 - Consider the following actual and forecast demand...Ch. 4 - As you can see in the following table, demand for...Ch. 4 - Following are two weekly forecasts made by two...Ch. 4 - Refer to Solved Problem 4.1 on page 138. a. Use a...Ch. 4 - Solved example 4.1 Sales of Volkswagens popular...Ch. 4 - Refer to Solved Problem 4.1. Using smoothing...Ch. 4 - Consider the following actual (At) and forecast...Ch. 4 - Income at the architectural firm Spraggins and...Ch. 4 - Question 4.20 Resolve Problem 4.19 with =.1 and ...Ch. 4 - Question 4.21 Refer to the trend-adjusted...Ch. 4 - Question 4.22 Refer to Problem 4.21. Complete the...Ch. 4 - Question 4.23 Sales of quilt covers at Bud Baniss...Ch. 4 - Question 4.25 The following gives the number of...Ch. 4 - Prob. 25PCh. 4 - Question 4.27 George Kyparisis owns a company...Ch. 4 - Question 4.28 Attendance at Orlandos newest...Ch. 4 - Question 4.29 North Dakota Electric Company...Ch. 4 - Question 4.33 The number of internal disk drives...Ch. 4 - Dr. Lillian Fok, a New Orleans psychologist,...Ch. 4 - Emergency calls to the 911 system of Durham, North...Ch. 4 - Using the 911 call data in Problem 4.43, forecast...Ch. 4 - Question 4.47 Storrs Cycles has just started...Ch. 4 - Question 4.49 Boulanger Savings and Loan is proud...Ch. 4 - Question 4.24 Mark Gershon, owner of a musical...Ch. 4 - Lori Cook has developed the following forecasting...Ch. 4 - Prob. 45PCh. 4 - Question 4.32 The following data relate the sales...Ch. 4 - Question 4.34 The number of auto accidents in...Ch. 4 - Question 4.35 Rhonda Clark, a Slippery Rock,...Ch. 4 - Accountants at the Tucson firm, Larry Youdelman,...Ch. 4 - Sales of tablet computers at Ted Glickmans...Ch. 4 - Question 4.38 City government has collected the...Ch. 4 - Using the data in Problem 4.39, apply linear...Ch. 4 - Bus and subway ridership for the summer months in...Ch. 4 - Thirteen students entered the business program at...Ch. 4 - Question 4.48 Dave Fletcher, the general manager...Ch. 4 - The following are monthly actual and forecast...Ch. 4 - Prob. 1CSCh. 4 - Prob. 2CSCh. 4 - Prob. 3CSCh. 4 - For its first 2 decades of existence, the NBAs...Ch. 4 - For its first 2 decades of existence, the NBAs...Ch. 4 - For its first 2 decades of existence, the NBAs...Ch. 4 - For its first 2 decades of existence, the NBAs...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...
Additional Business Textbook Solutions
Find more solutions based on key concepts
The best fits using exponential smoothing, trend analysis, and linear regression for the given data. Introducti...
Principles of Operations Management: Sustainability and Supply Chain Management (10th Edition)
Consider the sales data for Computer Success given in Problem 7. Use a 3-month weighted moving average to forec...
Operations Management: Processes and Supply Chains (11th Edition)
Consider the sales data for Computer Success given in Problem 7. Use a 3-month weighted moving average to forec...
Operations Management: Processes and Supply Chains (12th Edition) (What's New in Operations Management)
Small Business Analysis Purpose: To help you understand the importance of cash flows in the operation of a smal...
Financial Accounting, Student Value Edition (5th Edition)
1-1. Define marketing and outline the steps in the marketing process. (AASCB: Communication)
Marketing: An Introduction (12th Edition)
Do you think the sales growth will continue to be strong for vinyl sales? Why or why not?
Principles of 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
- 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?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_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_forwardUnder what conditions might a firm use multiple forecasting methods?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_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 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_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_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 file P13_25.xlsx contains the quarterly numbers of applications for home mortgage loans at a branch office of Northern Central Bank. 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? Is it guaranteed to produce better forecasts for the future?arrow_forwardSeptember 14 September 21 September 28 October 5 412 381 371 378 a) The forecasted demand for the week of October 12 using a 3-week moving average=pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.15, 0.35, and 0.50, using 0.50 for the most recent week, the forecasted demand for the week of October 12 = pints (round your response to two decimal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.)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