Simple linear regression results: Dependent Variable: Heart. Disease Independent Variable: Biking Heart. Disease = 18.115809 - 0.20845321 Biking Sample size: 68 R (correlation coefficient) = -0.94616452 R-sq = 0.8952273 Estimate of error standard deviation: 1.5273175 Correlation between Biking and Heart. Disease is: -0.94616452. Correlation between Smoking and Heart. Disease is: 0.32421. 1) State r 2 (i.e., the coefficient of determination) for “Biking” and “Heart.Disease” and explain what this value means in context of the data set.

Simple linear regression results: Dependent Variable: Heart. Disease Independent Variable: Biking Heart. Disease = 18.115809 - 0.20845321 Biking Sample size: 68 R (correlation coefficient) = -0.94616452 R-sq = 0.8952273 Estimate of error standard deviation: 1.5273175 Correlation between Biking and Heart. Disease is: -0.94616452. Correlation between Smoking and Heart. Disease is: 0.32421. 1) State r 2 (i.e., the coefficient of determination) for “Biking” and “Heart.Disease” and explain what this value means in context of the data set.

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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Simple linear regression results:

Dependent Variable: Heart. Disease
Independent Variable: Biking
Heart. Disease = 18.115809 - 0.20845321 Biking
Sample size: 68
R (correlation coefficient) = -0.94616452
R-sq = 0.8952273
Estimate of error standard deviation: 1.5273175

Correlation between Biking and Heart. Disease is: -0.94616452.

Correlation between Smoking and Heart. Disease is: 0.32421.

1) State r 2 (i.e., the coefficient of determination) for “Biking” and “Heart.Disease” and explain what this value means in context of the data set.

Definition Definition Relationship between two independent variables. A correlation tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

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