Listed below are numbers of enrolled students (in thousands) and numbers of campus burglaries for randomly selected large colleges in a recent year.
Enrollment | 32 | 31 | 53 | 28 | 27 | 36 | 42 | 30 | 34 | 46 |
Burglaries | 103 | 103 | 86 | 57 | 32 | 131 | 157 | 20 | 27 | 161 |
The best-fit line based on this data is:
burglaries = 3.47 enrollment - 36.77
with r2 = 0.315
Answer the following questions:
How much of the variation in burglaries can be accounted for by the best-fit line? [ Select ] ["0.315%", "3.47%", "31.5%", "36.77%"]
The regression equation predicts the number of campus burglaries to [ Select ] ["increase", "decrease", "not change"] by [ Select ] ["0.315", "3.47", "36.77"] for each additional one thousand students on campus.
Predict the number of campus burglaries when enrollment is 40 (thousands of students):
Predicted burglariesenrollment=40 = [ Select ] ["102.03", "167.59", "175.57", "1474.27"]
The best-fit line based on this data is:
burglaries = 3.47 enrollment - 36.77
with r2 = 0.315
Answer the following questions:
31.5% of the variation in burglaries can be accounted for by the best-fit line
The regression equation predicts the number of campus burglaries to increase by 3.47 for each additional one thousand students on campus.
Predict the number of campus burglaries when enrollment is 40 (thousands of students):
Predicted burglaries enrollment= 3.47*40- 36.77 = 102.03
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