Practical Management Science
6th Edition
ISBN: 9781337406659
Author: WINSTON, Wayne L.
Publisher: Cengage,
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Chapter 14.2, Problem 11P
Summary Introduction
To perform: Classification using NeuralTools and run the algorithm for second time using only the top five variables.
Introduction: Simulation model is the digital prototype of the physical model that helps to
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A company that supplies gasoline to a city has recorded the weeklyusage (tons/week) for the past 3 years. The file BA3653GasolineRecord.xlsxcontains this record.
(c) In general, the company delivers the demanded gasoline to customersthat store it in their own facilities. However, the company would like toobtain its own storage tanks to better handle variability. The companyhas identified several solutions: a 500 ton, a 1000 ton, a 2000 ton and a3000 ton system, with each tank being proportionately more expensiveas its size grows. Given your predictions and the expected variability,what size of tank would you choose?(d) Reaching the city is sometimes hazardous due to weather conditions.Even with these challenges, the company estimates that the most thatshipments to the city may be delayed is 1 week. Given this information,which tank choice (of those in part c) do you think would be appropriate?
week
demand (tons)
1
1174.5
2
1316.2
3
1197
4
1127.3
5
1193.1
6
1260.7
7…
Let’s suppose that you have a set of time-series variables, and you want to model the relationship between them. Read the situations given below and answer the questions. (200 words)a) Explain the statistical test if the linear combination (of time-series variables) is I(0).b) Which statistical test can be applied if all the series are integrated of the same order I(1). Justify your answer
A golf club manufacturer is trying to determine how the price of a set of clubs affects the demand for clubs. The file P10_50.xlsx contains the price of a set of clubs and the monthly sales.
Assume the only factor influencing monthly sales is price. Fit the following three curves to these data: linear (Y = a + bX), exponential (Y = abX), and multiplicative (Y = aXb). Which equation fits the data best?
Interpret your best-fitting equation.
Using the best-fitting equation, predict sales during a month in which the price is $470.
File data:
Price
Demand
$400
20,000
$420
19,000
$440
17,000
$460
16,000
$500
14,000
$380
22,000
$290
31,000
$340
26,000
$220
41,000
$700
6,000
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