Operations Management
11th Edition
ISBN: 9780132921145
Author: Jay Heizer
Publisher: PEARSON
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Chapter 4, Problem 10DQ
What is the primary difference between a time-series model and an associative model?
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What is the difference between a causal model and a time-series model?
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Chapter 4 Solutions
Operations Management
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 - 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 4.24 Mark Gershon, owner of a musical...Ch. 4 - Question 4.25 The following gives the number of...Ch. 4 - Prob. 26PCh. 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 - Lori Cook has developed the following forecasting...Ch. 4 - Prob. 31PCh. 4 - Question 4.32 The following data relate the sales...Ch. 4 - Question 4.33 The number of internal disk drives...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 - Dr. Lillian Fok, a New Orleans psychologist,...Ch. 4 - Using the data in Problem 4.39, apply linear...Ch. 4 - Bus and subway ridership for the summer months in...Ch. 4 - CEO John Goodale, at Southern Illinois Power and...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 - The following are monthly actual and forecast...Ch. 4 - Thirteen students entered the business program at...Ch. 4 - Question 4.47 Storrs Cycles has just started...Ch. 4 - Question 4.48 Dave Fletcher, the general manager...Ch. 4 - Question 4.49 Boulanger Savings and Loan is proud...Ch. 4 - Case study Southwestern University: (B) This...Ch. 4 - Case study Southwestern University: (B) This...Ch. 4 - Southwestern University: (B) This integrated case...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 - 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...
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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_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_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_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 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_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
- What is the distinction between a dependent variable and an independent variable?arrow_forwardwhat do the standardized regression weights or coefficients tell you about the ability of the predictors to predict the dependent variable?arrow_forwardIn comparison to causal techniques, what are the fundamental assumptions when utilizing predictive time series techniques?arrow_forward
- Explain the compromise between responsiveness and stability in a predictive system using data from time series.arrow_forwardsniparrow_forwardA pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales during the last 15 days were as follows:Day 1 2 3 4 5 6 7 8 9Number sold 36 38 42 44 48 49 50 49 52Day 10 11 12 13 14 15Number sold 48 52 55 54 56 57a. Which method would you suggest using to predict future sales—a linear trend equation or trend-adjusted exponential smoothing? Why? b. If you learn that on some days the store ran out of the specific pain reliever, would that knowledge cause you any concern? Explain c. Assume that the data refer to demand rather than sales. Using trend-adjusted smoothing with an initial forecast of 50 for day 8, an initial trend estimate of 2, and α = β = .3, develop forecasts for days 9 through 16. What is the MSE for the eight forecasts for which there are actual data?arrow_forward
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