Practical Management Science
6th Edition
ISBN: 9781337406659
Author: WINSTON, Wayne L.
Publisher: Cengage,
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Question
Chapter 13, Problem 46P
a)
Summary Introduction
To determine: The relationship between units shipped and monthly shipping cost.
Introduction: Simulation model is the digital prototype of the physical model that helps to
b)
Summary Introduction
To determine: Whether the error pattern is unusual.
Introduction: Simulation model is the digital prototype of the physical model that helps to forecast the performance of the system or model in the real world.
c)
Summary Introduction
To determine: The effect of trucking strike on part (a) and part (b).
Introduction: Simulation model is the digital prototype of the physical model that helps to forecast the performance of the system or model in the real world.
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A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales duringthe last 15 days wereDay: 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 trendadjustedexponential smoothing? Why?b. If you learn that on some days the store ran out of the specific pain reliever, would that knowledgecause you any concern? Explain.c. Assume that the data refer to demand rather than sales. Using trend-adjusted smoothing with aninitial forecast of 50 for week 8, an initial trend estimate of 2, and .3, develop forecastsfor days 9 through 16. What is the MSE for the eight forecasts for which there are actual data?
A 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?
To better plan for future growth of the restaurant, Karen needs to develop a system that will enable her to forecast food and beverage sales by month for up to one year in advance. Table shows the value of food and beverage sales ($1000s) for the first three years of operation.
Food and Beverage Sales for the Vintage Restaurant ($1000s)
Month
First Year
Second Year
Third Year
January
242
263
282
February
235
238
255
March
232
247
265
April
178
193
205
May
184
193
210
June
140
149
160
July
145
157
166
August
152
161
174
September
110
122
126
October
130
130
148
November
152
167
173
December
206
230
235
Managerial Report
Perform an analysis of the sales data for the Vintage Restaurant. Prepare a report for Karen that summarizes your findings, forecasts, and recommendations. Include the following:
A time series plot. Comment on the underlying pattern in the time series.…
Chapter 13 Solutions
Practical Management Science
Ch. 13.3 - The file P13_01.xlsx contains the monthly number...Ch. 13.3 - The file P13_02.xlsx contains five years of...Ch. 13.3 - The file P13_03.xlsx contains monthly data on...Ch. 13.3 - The file P13_04.xlsx lists the monthly sales for a...Ch. 13.3 - Management of a home appliance store wants to...Ch. 13.3 - Do the sales prices of houses in a given community...Ch. 13.3 - Prob. 7PCh. 13.3 - The management of a technology company is trying...Ch. 13.3 - Prob. 9PCh. 13.3 - Sometimes curvature in a scatterplot can be fit...
Ch. 13.4 - Prob. 12PCh. 13.4 - A trucking company wants to predict the yearly...Ch. 13.4 - An antique collector believes that the price...Ch. 13.4 - Stock market analysts are continually looking for...Ch. 13.4 - Suppose that a regional express delivery service...Ch. 13.4 - The owner of a restaurant in Bloomington, Indiana,...Ch. 13.6 - The file P13_19.xlsx contains the weekly sales of...Ch. 13.6 - The file P13_20.xlsx contains the monthly sales of...Ch. 13.6 - The file P13_21.xlsx contains the weekly sales of...Ch. 13.6 - The file P13_22.xlsx contains total monthly U.S....Ch. 13.7 - You have been assigned to forecast the number of...Ch. 13.7 - Simple exponential smoothing with = 0.3 is being...Ch. 13.7 - The file P13_25.xlsx contains the quarterly...Ch. 13.7 - The file P13_26.xlsx contains the monthly number...Ch. 13.7 - The file P13_27.xlsx contains yearly data on the...Ch. 13.7 - The file P13_28.xlsx contains monthly retail sales...Ch. 13.7 - The file P13_29.xlsx contains monthly time series...Ch. 13.7 - A version of simple exponential smoothing can be...Ch. 13 - Prob. 31PCh. 13 - Prob. 32PCh. 13 - Management of a home appliance store would like to...Ch. 13 - A small computer chip manufacturer wants to...Ch. 13 - The file P13_35.xlsx contains the amount of money...Ch. 13 - Prob. 36PCh. 13 - Prob. 37PCh. 13 - Prob. 39PCh. 13 - The Baker Company wants to develop a budget to...Ch. 13 - Prob. 41PCh. 13 - The file P13_42.xlsx contains monthly data on...Ch. 13 - Prob. 43PCh. 13 - Prob. 44PCh. 13 - Prob. 45PCh. 13 - Prob. 46PCh. 13 - Prob. 49P
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- 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_20.xlsx contains the monthly sales of iPod cases at an electronics store for a two-year period. Use the moving averages method, with spans of your choice, to forecast sales for the next six months. Does this method appear to track sales well? If not, what might be the reason?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_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_21.xlsx contains the weekly sales of rakes at a hardware store for a two-year period. Use the moving averages method, with spans of your choice, to forecast sales for the next 30 weeks. Does this method appear to track sales well? If not, what might be the reason?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
- Stock market analysts are continually looking for reliable predictors of stock prices. Consider the problem of modeling the price per share of electric utility stocks (Y). Two variables thought to influence this stock price are return on average equity (X1) and annual dividend rate (X2). The stock price, returns on equity, and dividend rates on a randomly selected day for 16 electric utility stocks are provided in the file P13_15.xlsx. Estimate a multiple regression equation using the given data. Interpret each of the estimated regression coefficients. Also, interpret the standard error of estimate and the R-square value for these data.arrow_forwardThe file P13_19.xlsx contains the weekly sales of a particular brand of paper towels at a supermarket for a one-year period. a. Using a span of 3, forecast the sales of this product for the next 10 weeks with the moving averages method. How well does this method with span 3 forecast the known observations in this series? b. Repeat part a with a span of 10. c. Which of these two spans appears to be more appropriate? Justify your choice.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
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