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To estimate ages of trees, rangers use a simple regression model that relates the tree diameter (inches) to their age (years). The model is useful because tree diameter has an association to tree age (count of cross section rings). 8 trees were sampled. The regression model is:                    TreeAge= -0.15228+6.451 (Diameter)   d) If in fact, the tree age is 76 years for a tree with diameter 9.5 inches, the residual is approximately       ["", ""]  . The age has been a(n) [a7]. e) If the correlation , then the coefficient of determination is [a8].

To estimate ages of trees, rangers use a simple regression model that relates the tree diameter (inches) to their age (years). The model is useful because tree diameter has an association to tree age (count of cross section rings). 8 trees were sampled. The regression model is:                    TreeAge= -0.15228+6.451 (Diameter)   d) If in fact, the tree age is 76 years for a tree with diameter 9.5 inches, the residual is approximately       ["", ""]  . The age has been a(n) [a7]. e) If the correlation , then the coefficient of determination is [a8].

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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To estimate ages of trees, rangers use a simple regression model that relates the tree diameter (inches) to their age (years). The model is useful because tree diameter has an association to tree age (count of cross section rings). 8 trees were sampled.

The regression model is:                   

TreeAge= -0.15228+6.451 (Diameter)

 

d) If in fact, the tree age is 76 years for a tree with diameter 9.5 inches, the residual is approximately       ["", ""]  . The age has been a(n) [a7].

e) If the correlation , then the coefficient of determination is [a8].

Formulas: r = ±VR? Residual = actual y – predicted y
Transcribed Image Text:Formulas: r = ±VR? Residual = actual y – predicted y
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