A multiple regression analysis produced the following tables. Summary Output Regression Statistics Multiple R 0.978724022 R Square 0.957900711 Adjusted R Square 0.952287472 Standard Error 67.67055418 Observations 18 ANOVA df SS MS F Significance F Regression 2 1562918.941 781459.5 170.6503 4.80907E-11 Residual 15 68689.55855 4579.304 Total 17 1631608.5 Coefficients Standard Error t Stat P-value Intercept 1959.709718 306.4905312 6.39403 1.21E-05 X1 -0.469657287 0.264557168 -1.77526 0.096144 X2 -2.163344882 0.278361425 -7.77171 1.23E-06 These results indicate that ____________. x1 is significant at the 10% level the intercept is not significant at 10% level none of the predictor variables are significant at the 10% level x2 is significant at the 10% level each predictor variable is significant at the 10% level
A multiple regression analysis produced the following tables. Summary Output Regression Statistics Multiple R 0.978724022 R Square 0.957900711 Adjusted R Square 0.952287472 Standard Error 67.67055418 Observations 18 ANOVA df SS MS F Significance F Regression 2 1562918.941 781459.5 170.6503 4.80907E-11 Residual 15 68689.55855 4579.304 Total 17 1631608.5 Coefficients Standard Error t Stat P-value Intercept 1959.709718 306.4905312 6.39403 1.21E-05 X1 -0.469657287 0.264557168 -1.77526 0.096144 X2 -2.163344882 0.278361425 -7.77171 1.23E-06 These results indicate that ____________. x1 is significant at the 10% level the intercept is not significant at 10% level none of the predictor variables are significant at the 10% level x2 is significant at the 10% level each predictor variable is significant at the 10% level
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
A multiple
| Summary Output | ||||||||||
| Regression Statistics | ||||||||||
|
Multiple R
|
0.978724022 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|
R Square
|
0.957900711 | |||||||||
|
Adjusted R Square
|
0.952287472 | |||||||||
|
Standard Error
|
67.67055418 | |||||||||
|
Observations
|
18 | |||||||||
| ANOVA | ||||||||||
|
df
|
SS
|
MS
|
F
|
Significance F
|
||||||
|
Regression
|
2
|
1562918.941 |
781459.5
|
170.6503
|
4.80907E-11
|
|||||
|
Residual
|
15
|
68689.55855 |
4579.304
|
|||||||
|
Total
|
17
|
1631608.5 | ||||||||
|
Coefficients
|
Standard Error
|
t Stat
|
P-value
|
|||||||
|
Intercept
|
1959.709718
|
306.4905312
|
6.39403
|
1.21E-05
|
||||||
|
X1
|
-0.469657287
|
0.264557168
|
-1.77526
|
0.096144
|
||||||
|
X2
|
-2.163344882
|
0.278361425
|
-7.77171
|
1.23E-06
|
These results indicate that ____________.
x1 is significant at the 10% level
the intercept is not significant at 10% level
none of the predictor variables are significant at the 10% level
x2 is significant at the 10% level
each predictor variable is significant at the 10% level
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