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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 (1) and distance traveled (2) 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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Using the data in Problem 4.30, apply linear regression to study the relationship between the robbery rate and Dr. Fok’s patient load. If the robbery rate increases to 131.2 in year 11, how many phobic patients will Dr. Fok treat? If the robbery rate drops to 90.6, what is the patient projection?

Problem 4.30

Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Fok has seen each year for the past 10 years. It also indicates what the robbery rate was in New Orleans during the same year:

Using trend (linear regression) analysis, predict the number of patients Dr. Fok will see in years 11 and 12 as a function of time. How well does the model fit the data?

 
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Dave Fletcher, the general manager of North Carolina Engineering Corporation (NCEC), thinks that his firm’s engineering services contracted to highway construction firms are directly related to the volume of highway construction business contracted with companies in his geographic area. He wonders if this is really so, and if it is, can this information help him plan his operations better by forecasting the quantity of his engineering services required by construction firms in each quarter of the year? The following table presents the sales of his services and total amounts of contracts for highway construction over the past eight quarters:

a) Using this data, develop a regression equation for predicting the level of demand of NCEC’s services.

b) Determine the coefficient of correlation and the standard error of the estimate.

 
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Bus and subway ridership for the summer months in London, England, is believed to be tied heavily to the number of tourists visiting the city. During the past 12 years, the data on the next page have been obtained:

a) Plot these data and decide if a linear model is reasonable.

b) Develop a regression relationship.

c) What is expected ridership if 10 million tourists visitLondon in a year?

d) Explain the predicted ridership if there are no tourists at all.

e) What is the standard error of the estimate?

f) What is the model’s correlation coefficient and coefficient of determination?

 
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