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 ($$) 70000 60000 50000 40000 30000 20000 10000 0 Males Smokers, aged 40 to 64 y = 1487x-9399.7 R² = 0.6501 18 23 28 33 38 43 BMI Use the regression equation to predict the dollar amount of claims for a client with a BMI of 29.28. Write your answer as a number and do NOT round. Please do not use dollar signs, equaul signs, commas, or any other symbols!
The graph below includes the results of a linear regression using this data. (For example, the client identified with the grey square in the graph has a BMI of 29.28 and has cost the insurance company $22,411 over the previous 60 months.) Insurance Charges ($$) 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 Use the regression equation to predict the dollar amount of claims for a client with a BMI of 29.28. Write your answer as a number and do NOT round. Please do not use dollar signs, equaul signs, commas, or any other symbols!
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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