Multiple R 09161 R Square 0.8392 Adjusted R Square 0 8109 Standard Error 20.1451 Observations 21 ANOVA df SS MS F Regression 3 36011.50 12003.83 29.58 0.0000 Residual 17 6899.00 405 82 Total 20 42910 50 Coefficients Std. Error Stat P-value Intercept 3 75 27.36 0.137 0.8927 XI 3.73 O.S1 4.607 0.0003 X2 49.72 15.69 3 169 0.0056 X3 -0 91 0.38 -2.403 0.0279 If we remove any of the 3 predictors from the model the R-Square would decrease Which would cause it to drop the most? O remove X1 O remove X3 O remove X2
Multiple R 09161 R Square 0.8392 Adjusted R Square 0 8109 Standard Error 20.1451 Observations 21 ANOVA df SS MS F Regression 3 36011.50 12003.83 29.58 0.0000 Residual 17 6899.00 405 82 Total 20 42910 50 Coefficients Std. Error Stat P-value Intercept 3 75 27.36 0.137 0.8927 XI 3.73 O.S1 4.607 0.0003 X2 49.72 15.69 3 169 0.0056 X3 -0 91 0.38 -2.403 0.0279 If we remove any of the 3 predictors from the model the R-Square would decrease Which would cause it to drop the most? O remove X1 O remove X3 O remove X2
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question

Transcribed Image Text:Regression StatisTics
Multiple R
0.9161
R Square
0.8392
Adjusted R Square
0 8109
Standard Error
20.1451
Observations
21
ANOVA
df
SS
MS
F
Regression
3
36011.50 12003.83
29.58
0.0000
Residual
17
6899 00
405.82
Total
20
42910.50
Coefficients
Std. Error
t Stat
P-value
Intercept
375
27.36
0.137
0.8927
XI
3.73
O.81
4.607
0.0003
X2
49.72
15.69
3 169
0.0056
X3
-0 91
0.38
-2.403
0.0279
If we remove any of the 3 predictors from the model the R-Square would decrease Which would cause it to drop the
most?
O remove X1
remove X3.
remove X2
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