Q.3. A rental management executive has collected data on square footage and monthly rental fee for 12 apartments in his city. Considering square footage as the independent variable and monthly rental fee as the dependent variable: The data is given below. (14 points) Square footage 37 14 9 12 10 14 15 8 11 9 13 10 Monthly 2.65 3.21 3.0 4.21 2.76 3.43 4 2.22 2.88 2.95 3.56 2.98 rental fee

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
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Q.3. A rental management executive has collected data on square footage and monthly rental
fee for 12 apartments in his city. Considering square footage as the independent variable and
monthly rental fee as the dependent variable: The data is given below.
(14 points)
Square
footage
37
14
9
12
10
14
15 8
11
13
10
|Monthly
2.65
3.21
3.0
| 4.21 2.76 3.43 4
2.22 2.88 2.95
3.56
2.98
rental fee
a. Generate a scatter diagram that includes the best-fit linear equation for these data.
b. Does there appear to be any relationship between the variables? If so, is the relationship
direct or inverse?
c. Interpret the slope of the equation generated in part (a).
d. Viewing the scatter diagram and equation in part (a), do you think there are any apartments
that seem to have an unusually high or an unusually low rental fee compared to what would be
predicted for an apartment of their size? Are there any variables that are not included in the data
that might help explain such a differential? If so, what might they be?
Transcribed Image Text:Q.3. A rental management executive has collected data on square footage and monthly rental fee for 12 apartments in his city. Considering square footage as the independent variable and monthly rental fee as the dependent variable: The data is given below. (14 points) Square footage 37 14 9 12 10 14 15 8 11 13 10 |Monthly 2.65 3.21 3.0 | 4.21 2.76 3.43 4 2.22 2.88 2.95 3.56 2.98 rental fee a. Generate a scatter diagram that includes the best-fit linear equation for these data. b. Does there appear to be any relationship between the variables? If so, is the relationship direct or inverse? c. Interpret the slope of the equation generated in part (a). d. Viewing the scatter diagram and equation in part (a), do you think there are any apartments that seem to have an unusually high or an unusually low rental fee compared to what would be predicted for an apartment of their size? Are there any variables that are not included in the data that might help explain such a differential? If so, what might they be?
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