Calculate the estimated R2 and state why we should consider using adjusted R2 instead of R2 in the setting of multiple linear regression?
Calculate the estimated R2 and state why we should consider using adjusted R2 instead of R2 in the setting of multiple linear regression?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Calculate the estimated R2 and state why we should consider using adjusted R2 instead of R2 in the setting of multiple linear regression?
Transcribed Image Text:Response Height
Whole Model
Actual by Predicted Plot
80
Height Actual
75
70-
Height Residual
65
60
Effect Summary
Source LogWorth
LeftFoot
LeftArm
HeadCirc
Nose
60
NO
Residual by Predicted Plot
6
4
-4
65
70
75
Height Predicted RMSE=2.1834 RSq=0.77
PValue=<.0001
60
6.885
4.679
0.227
0.116
Summary of Fit
RSquare
RSquare Adj
Source
Model
Error
C. Total
65
Root Mean Square Error
Mean of Response
Observations (or Sum Wgts)
Analysis of Variance
70
Height Predicted
0.774018
0.755939
2.183363
68.30909
55
Sum of
DF
Squares Mean Square
816.3917
4
204.098
4.767
50
238.3537
54 1054.7455
80
F Ratio
42.8141
Prob > F
<.0001*
Parameter Estimates
Term
Estimate Std Error t Ratio Prob>|t|
Intercept 18.502649 7.830309 2.36 0.0221*
LeftArm 0.8020485 0.170743 4.70 <.0001*
Nose
-0.1474 0.492332 -0.30 0.7659
HeadCirc 0.0805215 0.149519 0.54 0.5926
LeftFoot 0.9973003 0.162299 6.14 <.0001*
PValue
0.00000
0.00002
0.59260
0.76588
75
80
LeftArm
Leverage Plot
80
75
75
L DE L
70
70
65
60
22
26
28
24
LeftArm Leverage, P<.0001
30
Nose
Leverage Plot
80
75
70
65
60
4
5
6
Nose Leverage, P=0.7659
7
HeadCirc
Leverage Plot
80
75
70
65
60
52
54
ܗܘܐ
56
58
60
HeadCirc Leverage, P=0.5926
LeftFoot
Leverage Plot
80
62
60
20
22
24
26
28
LeftFoot Leverage, P<.0001
30
32
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