Operations Management
11th Edition
ISBN: 9780132921145
Author: Jay Heizer
Publisher: PEARSON
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Chapter 4, Problem 36P
Accountants at the Tucson firm, Larry Youdelman, CPAs, believed that several traveling executives were submitting unusually high travel vouchers when they returned from business trips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple-regression equation relating expected travel cost to number of days on the road (x1) and distance traveled (x2) in miles:
The coefficient of correlation computed was .68.
- a. If Barbara Downey returns from a 300-mile trip that took her out of town for 5 days, what is the expected amount she should claim as expenses?
- b. Downey submitted a reimbursement request for $685. What should the accountant do?
- c. Should any other variables be included? Which ones? Why?
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Students have asked these similar questions
The following multiple regression printout can be used to predict a person's height (in inches) given his or her shoe size and gender, where gender = 1 for males and 0 for females.
Regression Analysis: Height Versus Shoe Size,
Gender
Coefficients
Term
Coef
Constant
55.28
SE Coef
1.04
T-Value
P-Value
Shoe Size
0.105
Gender
0.268
0.12
0.489
53.1
0.875
0.000
0.000
0.548
0.000
(a) The dependent variable in this regression is which of the following?
height
gender
shoe size
constant
(b)
What is the regression coefficient of shoe size?
(c) What is the regression coefficient of gender?
In comparison to causal techniques, what are the fundamental assumptions when utilizing predictive time series techniques?
Explain three (3) of the general assumptions of a Regression (Least Squares) model.
Chapter 4 Solutions
Operations Management
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