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Topic 6 – Multiple Regression (Weeks 11 & 12) BUS 240 Data Analysis for managers

Topic 6 – Multiple Regression (Weeks 11 & 12) BUS 240 Data Analysis for managers

Topic 6 – Multiple Regression (Weeks 11 & 12) BUS 240 Data Analysis for managers

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HOA 3
Name___________________________________
For short answer, number and provide answers on an attached sheet of paper.
SHORT ANSWER. Write the word or phrase that best completes each statement or answers the
question.
1) Mary examined a random sample of Friday withdrawals from a college campus
ATM. She hypothesized that the mean was less than $100. The results shown
below are from MegaStat. What would Mary conclude from this test? Explain
carefully.
1)
2) The table below compares two samples taken to compare the mean age of
individuals who purchased the iPhone 3G at two AT&T store locations. Very
briefly, what conclusions can you draw?
2)
1
MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the
question.
3) The regression equation Salary = 45,000 + 1500 YearsExperience + 2800 YearsCollege
describes employee salaries at Terminus Fissile Labs. The standard error is 2500. Lars
has 15 years’ experience and 4 years of college. His salary is $70,500. If this regression
is valid, we conclude that:
A) Lars is overpaid, and his salary is an outlier.
B) Lars is overpaid, but is not an outlier.
C) Lars is underpaid, and his salary is an outlier.
D) Lars is underpaid, but is not an outlier.
3)
SHORT ANSWER. Write the word or phrase that best completes each statement or answers the
question.
4) Pedro became interested in vehicle fuel efficiency, so he performed a simple
regression using 93 cars to estimate the model CityMPG = ?0 + ?1 Weight,
where Weight is the weight of the vehicle in pounds. His results are shown
below. Write a brief analysis of these results, using what you have learned in
this chapter. Is the intercept meaningful in this regression? Make a prediction of
CityMPG when Weight = 3000 and also when Weight = 4000. Do these
predictions seem believable? If you could make a car 1000 pounds lighter, what
change would you predict in its CityMPG?
2
4)
5) Bob analyzed the trend in the value of his investment portfolio over the last 16
quarters. (1) Translate each trend into plain English that a business person could
understand. (2) Use each fitted trend to make a mathematical prediction for
Bob’s investment portfolio’s value in period 20. (3) Which trend model seems
most reasonable (or more than one)? What would Occam’s Razor say?
3
5)
4

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