Question
You want to construct a multiple linear regression model. The dependent variable is Y and independent...
You want to construct a multiple linear regression model. The dependent variable is Y and independent variables are x1 and x2. The samples and STATA outputs are provided:
How would you make an ANOVA from the following information?
| Y | X1 | X2 |
| 3 | 2 | 1 |
| 4 | 1 | 2 |
| 6 | 3 | 3 |
| 6 | 3 | 4 |
| 7 | 4 |
5 |
STATA
| Y | Coef. | Std. Err. | t | P> abs. value (t) | 95% confidence interval |
| X1 | 0.25 | 0.4677072 | 0.53 | 0.646 | -1.762382 , 2.262382 |
| X2 | 0.85 | 0.3372684 | 2.52 | 0.128 | -.601149 , 2.301149 |
| _cons | 2 | 0.7245688 | 2.76 | 0.110 | -1.117568 , 5.117568 |
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You want to construct a multiple linear regression model. The dependent variable is Y and independent...
You want to construct a multiple linear regression model. The
dependent variable is Y and independent variables are x1 and x2.
The samples and STATA outputs are provided:
Y
X1
X2
3
2
1
4
1
2
6
3
3
6
3
4
7
4
5
STATA
Y
Coef.
Std. Err.
t
P> abs. value (t)
95% confidence interval
X1
0.25
0.4677072
0.53
0.646
-1.762382 , 2.262382
X2
0.85
0.3372684
2.52
0.128
-.601149 , 2.301149
_cons
2
0.7245688
2.76
0.110...
You want to construct a multiple linear regression model. The dependent variable is Y and independent...
You want to construct a multiple linear regression model. The
dependent variable is Y and independent variables are x1 and x2.
The samples and STATA outputs are provided:
Y
X1
X2
3
2
1
4
1
2
6
3
3
6
3
4
7
4
5
STATA
Y
Coef.
Std. Err.
t
P> abs. value (t)
95% confidence interval
X1
0.25
0.4677072
0.53
0.646
-1.762382 , 2.262382
X2
0.85
0.3372684
2.52
0.128
-.601149 , 2.301149
_cons
2
0.7245688
2.76
0.110...
(By Hand) For the dependent variable Y and the independent variables X1 and X2, the linear...
(By Hand) For the dependent variable Y and the independent
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X2
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6
6.8
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6.2
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8.5
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9.3
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5.7
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5.4
You are given the following partial Stata output: regress y x z Source | SS df...
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-------------+---------------------------------------
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810
1
Residual | 270
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-------------+----------------------------------------
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------------------------------------------------------------------------------
y | Coef. Std. Err. t P>|t| [95%
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