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1. State your regression model (least-squares line). y=360.3622x + 4839.606 2. Use your model to predict the per capita health care expenditures for the year 2015. y = 10245.039 dollars 3. Use your model to predict when per capita health care expenditures will reach $13,000.

1. State your regression model (least-squares line). y=360.3622x + 4839.606 2. Use your model to predict the per capita health care expenditures for the year 2015. y = 10245.039 dollars 3. Use your model to predict when per capita health care expenditures will reach $13,000.

Advanced Engineering Mathematics
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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Directions: Construct a Regression Model for the following data. Years (after 2000) Dollars 9 8175 10 8428 12 8996 13 9255 U.S. Per Capita Health Care Expenditures 1. State your regression model (least-squares line). Y = 360.3622x + 4839.606 2. Use your model to predict the per capita health care expenditures for the year 2015. y = 10245.039 dollars 3. Use your model to predict when per capita health care expenditures will reach $13,000. When 23 During year 13000 Rounding: If you do round the numbers in your work, make sure you do it during your last step.
Transcribed Image Text:Directions: Construct a Regression Model for the following data. Years (after 2000) Dollars 9 8175 10 8428 12 8996 13 9255 U.S. Per Capita Health Care Expenditures 1. State your regression model (least-squares line). Y = 360.3622x + 4839.606 2. Use your model to predict the per capita health care expenditures for the year 2015. y = 10245.039 dollars 3. Use your model to predict when per capita health care expenditures will reach $13,000. When 23 During year 13000 Rounding: If you do round the numbers in your work, make sure you do it during your last step.
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