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1. An environmentalist would like to study the relationship between home energy usage
and the number of occupants. What would you expect regarding the correlation
between the cost of home energy usage and the number of occupants?
B
a. Negative correlation
b. Positive correlation
c. Close to 0 correlation
d. Correlation cannot be computed
2.
Which of the following correlation coefficients represents the strongest relationship?
C
a.
1.07
b.
0.78
c.
0.92
d.
0.14
e.
0.08
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QUESTIONS 3  4:
The number of firefighters it takes to control a fire has a strong,
linear, positive association (r = 0.79)
with the size of the fire.
3.
Which variable is the explanatory variable?
a. Size of fire
b. Number of fire trucks
c. Brightness of fire
d. Number of firefighters
e. Number of fires per year
4.
Which statement best interprets the correlation coefficient, r = 0.79, in this context?
a. As the size of the fire increases, the number of firefighters always increases.
b. The greater the increase in size of fire, the greater the decrease in damages.
c. The size of the fire causes the number of firefighters to increase.
d. As the size of the fire increases, the number of firefighters, on average, also
increases
e. It is impossible to interpret the correlation since one variable is categorical.
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MSIT 3000 Test 3 Version 1 Page 1
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View Full DocumentQUESTIONS 5  9
:
To help make a decision about possible replacement of aging
welding equipment used in a manufacturing process, you collected data on repairs
costs (in hundreds of dollars) and age of the welding machine (in months) for 37
machines.
Graphs and statistics support the appropriateness of the linear regression
model:
·
Repair Cost = 5.38+ 2.47 Age
5. To test whether the simple linear model is useful, we test
a. Whether the yintercept is different from 0.
b. Whether the yintercept is different from 1.
c.
Whether r
2
is large.
d. Whether the slope parameter is different from 0.
e. Whether the slope parameter is different from 1.
6.
Which of the following is a correct interpretation of the slope parameter estimate?
a.
As age increases by 1 month, repair costs increase on average by $538.
b.
As repair costs increase by $100, the machines are aging on average by 2.47
months.
c.
As repair costs increase by $247, the machines are 2.47 months older.
d.
As age increases by 1 month, repair costs increase on average by $247.
e.
When Age is 0, repair costs are predicted to be $247 during that month on
average.
7. If r = 0.673, which of the following is correct?
a.
67.3% of the variability in monthly repair costs can be explained by age.
b.
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 Fall '11
 kiM

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