Interpret the following graphs for multiple linear regression and comment on the validity of model assumptions

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
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Interpret the following graphs for multiple linear regression and comment on the validity of model assumptions

 

Residual
Residual
Percent
20
10
0
-10
20
10
0
-10
-20
25
20
15
10
5
0
no
T
-3 -2 -1
180 о
10 20 30 40
Predicted Value
0
Quantile
1
-18 -10 -2 6
Residual
T
2
O
0
3
T
14 22
Fit Diagnostics for BodyFat
RStudent
BodyFat
-2
50
40
30
20
10
0
30
20
10
0
。00,
-10-
0
A
10 20
Boo
A
Fit-Mean
0
Predicted Value
0
30 40
10 20
Predicted Value
00
0
30 40 50
Residual
0
0.0 0.4 0.8 0.0 0.4 0.8
Proportion Less
RStudent
Cook's D
2
O
-2
0.15
0.10
0.05
0.00
O
8
0
0.0 0.1
O
0.2 0.3
Leverage
0
the
0 50 100 150 200 250
Observation
Observations
252
Parameters
9
Error DF
243
MSE
34.95
R-Square
0.5169
Adj R-Square 0.501
Transcribed Image Text:Residual Residual Percent 20 10 0 -10 20 10 0 -10 -20 25 20 15 10 5 0 no T -3 -2 -1 180 о 10 20 30 40 Predicted Value 0 Quantile 1 -18 -10 -2 6 Residual T 2 O 0 3 T 14 22 Fit Diagnostics for BodyFat RStudent BodyFat -2 50 40 30 20 10 0 30 20 10 0 。00, -10- 0 A 10 20 Boo A Fit-Mean 0 Predicted Value 0 30 40 10 20 Predicted Value 00 0 30 40 50 Residual 0 0.0 0.4 0.8 0.0 0.4 0.8 Proportion Less RStudent Cook's D 2 O -2 0.15 0.10 0.05 0.00 O 8 0 0.0 0.1 O 0.2 0.3 Leverage 0 the 0 50 100 150 200 250 Observation Observations 252 Parameters 9 Error DF 243 MSE 34.95 R-Square 0.5169 Adj R-Square 0.501
BodyFat= -40.487 +0.3199 Age +0.2857 Neck +0.9816 Thigh +0.1323 Knee +0.0679 Ankle +0.1986 Biceps +0.4213 Forearm
-2.6906 Wrist
25
Residual
20
15
10-
0
-5
-10-
-15
++
+
+
0
+
+
25
50
75
100
++
+
125
150
Observation Number
+++
+
175
+
200
+
+
+
225
+
250
275
N
252
Rsq
0.5169
AdjRsq
0.5010
RMSE
5.9118
Transcribed Image Text:BodyFat= -40.487 +0.3199 Age +0.2857 Neck +0.9816 Thigh +0.1323 Knee +0.0679 Ankle +0.1986 Biceps +0.4213 Forearm -2.6906 Wrist 25 Residual 20 15 10- 0 -5 -10- -15 ++ + + 0 + + 25 50 75 100 ++ + 125 150 Observation Number +++ + 175 + 200 + + + 225 + 250 275 N 252 Rsq 0.5169 AdjRsq 0.5010 RMSE 5.9118
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