>USE "Z:\mydocs\ys209\yule.syd"
SYSTAT Rectangular file
Z:\mydocs\ys209\yule.syd,
created Wed Feb 17,
1999 at 09:34:32, contains variables:
UNION$
PAUP OUTRATIO
PROPOLD POP
>regress
>format 3
>rem Model 1
>model paup=constant+outratio
>estimate
Dep Var: PAUP
N: 32 Multiple R: 0.594 Squared multiple R: 0.353
Adjusted squared multiple
R: 0.331 Standard error of estimate: 13.483
Effect
Coefficient Std Error Std Coef
Tolerance t P(2 Tail)
CONSTANT
31.089 5.324
0.000 .
5.840 0.000
OUTRATIO
0.765 0.189
0.594 1.000 4.045
0.000
Analysis of Variance
Source
Sum-of-Squares df Mean-Square
F-ratio P
Regression
2973.751 1 2973.751
16.359 0.000
Residual
5453.468 30 181.782
-------------------------------------------------------------------------------
*** WARNING ***
Case
15 has large leverage (Leverage =
0.328)
Durbin-Watson D Statistic
1.853
First Order Autocorrelation
-0.018
>rem Model 2
>model paup=constant+outratio+propold
>estimate
Dep Var: PAUP
N: 32 Multiple R: 0.681 Squared multiple R: 0.464
Adjusted squared multiple
R: 0.427 Standard error of estimate: 12.486
Effect
Coefficient Std Error Std Coef
Tolerance t P(2 Tail)
CONSTANT
-27.822 24.588
0.000 . -1.132
0.267
OUTRATIO
0.718 0.176
0.558 0.988 4.075
0.000
PROPOLD
0.606 0.248
0.335 0.988 2.446
0.021
Analysis of Variance
Source
Sum-of-Squares df Mean-Square
F-ratio P
Regression
3906.190 2 1953.095
12.528 0.000
Residual
4521.029 29 155.898
-------------------------------------------------------------------------------
*** WARNING ***
Case
15 has large leverage (Leverage =
0.374)
Durbin-Watson D Statistic
1.970
First Order Autocorrelation
-0.051
>rem Model 3
>model paup=constant+outratio+propold+pop
>estimate
Dep Var: PAUP
N: 32 Multiple R: 0.835 Squared multiple R: 0.697
Adjusted squared multiple
R: 0.665 Standard error of estimate: 9.547
Effect
Coefficient Std Error Std Coef
Tolerance t P(2 Tail)
CONSTANT
63.188 27.144
0.000 .
2.328 0.027
OUTRATIO
0.752
0.135 0.584
0.985 5.572
0.000
PROPOLD
0.056
0.223 0.031
0.711 0.249
0.805
POP
-0.311
0.067 -0.570
0.719 -4.648 0.000
Analysis of Variance
Source
Sum-of-Squares df Mean-Square
F-ratio P
Regression
5875.320 3 1958.440
21.488 0.000
Residual
2551.899 28 91.139
-------------------------------------------------------------------------------
*** WARNING ***
Case
15 has large leverage (Leverage =
0.424)
Case
30 is an outlier (Studentized
Residual = 3.618)
Durbin-Watson D Statistic
2.344
First Order Autocorrelation
-0.177
>rem Model 4 (trimmed
model)
>model paup=constant+outratio+pop
>estimate
Dep Var: PAUP
N: 32 Multiple R: 0.835 Squared multiple R: 0.697
Adjusted squared multiple
R: 0.676 Standard error of estimate: 9.391
Effect
Coefficient Std Error Std Coef
Tolerance t P(2 Tail)
CONSTANT
69.659 7.685
0.000 .
9.065 0.000
OUTRATIO
0.756 0.132
0.587 1.000 5.736
0.000
POP
-0.320 0.056
-0.586 1.000 -5.730
0.000
Analysis of Variance
Source
Sum-of-Squares df Mean-Square
F-ratio P
Regression
5869.672 2 2934.836
33.278 0.000
Residual
2557.547 29 88.191
-------------------------------------------------------------------------------
*** WARNING ***
Case
15 has large leverage (Leverage =
0.420)
Case
30 is an outlier (Studentized
Residual = 3.326)
Case
32 has large leverage (Leverage =
0.390)
Durbin-Watson D Statistic
2.332
First Order Autocorrelation
-0.171