The graph below includes the results of a linear regression using this data. (For example, the client identified with the grey square in the graph has a BMI of 29.28 and has cost the insurance company $22,411 over the previous 60 months.) Insurance Charges ($$) 70000 60000 50000 40000 30000 20000 10000 0 Males Smokers, aged 40 to 64 y=1487x-9399.7 R² = 0.6501 18 23 28 33 38 43 BMI Interpret the value of the intercept of the regression line in the context of this question.

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
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Q2

The graph below includes the results of a linear regression using this data. (For example, the client
identified with the grey square in the graph has a BMI of 29.28 and has cost the insurance
company $22,411 over the previous 60 months.)
Insurance Charges ($$)
70000
60000
50000
40000
30000
20000
10000
0
Males Smokers, aged 40 to 64
y=1487x-9399.7
R² = 0.6501
18
23
28
33
38
43
BMI
Interpret the value of the intercept of the regression line in the context of this question.
Transcribed Image Text:The graph below includes the results of a linear regression using this data. (For example, the client identified with the grey square in the graph has a BMI of 29.28 and has cost the insurance company $22,411 over the previous 60 months.) Insurance Charges ($$) 70000 60000 50000 40000 30000 20000 10000 0 Males Smokers, aged 40 to 64 y=1487x-9399.7 R² = 0.6501 18 23 28 33 38 43 BMI Interpret the value of the intercept of the regression line in the context of this question.
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