A statistics student is studying if there is a relationship between the price of a used car and the number of miles it has been driven. She collects data for 20 cars of the Using the computer output, what is the equation of the least-squares regression line? same model with different mileage, and determines each car's price using a used car website. The analysis is given in the computer output. ý = -0.181 + 24157.2x ý 24157.2-0.181x ý = 2164.1 + 0.024x Predictor Сoef SE Coef t-ratio O ŷ = 0.024 + 2164.1x Constant 24157.2 2164.1 2.965 0.046 Mileage S 3860.7 R-Sq = 68.0% R-Sq(Adj) -0.181 0.024 5.377 0.000 = 67.5%

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 5PPS
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A statistics student is studying if there is a relationship
between the price of a used car and the number of miles
Using the computer output, what is the equation of the
least-squares regression line?
it has been driven. She collects data for 20 cars of the
ý = -0.181 + 24157.2x
same model with different mileage, and determines each
car's price using a used car website. The analysis is
ý = 24157.2 -0.181x
given in the computer output.
ý = 2164.1 + 0.024x
Predictor
Coef SE Coef
t-ratio
Oŷ = 0.024 + 2164.1x
Constant
24157.2
2164.1
2.965 0.046
Mileage
-0.181
0.024
5.377 0.000
S 3860.7 R-Sq = 68.0% R-Sq(Adj)
= 67.5%
Transcribed Image Text:A statistics student is studying if there is a relationship between the price of a used car and the number of miles Using the computer output, what is the equation of the least-squares regression line? it has been driven. She collects data for 20 cars of the ý = -0.181 + 24157.2x same model with different mileage, and determines each car's price using a used car website. The analysis is ý = 24157.2 -0.181x given in the computer output. ý = 2164.1 + 0.024x Predictor Coef SE Coef t-ratio Oŷ = 0.024 + 2164.1x Constant 24157.2 2164.1 2.965 0.046 Mileage -0.181 0.024 5.377 0.000 S 3860.7 R-Sq = 68.0% R-Sq(Adj) = 67.5%
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