17 Feb 98 SPSS for Unix, Release 5.0 (IBM RS/6000) Page 1
16:12:22 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
For IBM AIX 3.2. sigma.oac.ucla.edu SPSS ID 265665
-> TITLE CURVILINEAR REGRESSION--POLYNOMIAL EQUATION.
-> DATA LIST RECORDS=1
-> /Y 1-2 X 3-4.
This command will read 1 records from the command file
Variable Rec Start End Format
Y 1 1 2 F2.0
X 1 3 4 F2.0
-> COMPUTE X2=X**2.
-> COMPUTE X3=X**3.
-> BEGIN DATA
-> 3 2
-> 4 2
-> 6 2
-> 5 2
-> 7 4
-> 10 4
-> 10 4
-> 13 6
-> 14 6
-> 15 6
-> 16 8
-> 17 8
-> 21 8
-> 1810
-> 1910
-> 2010
-> 1912
-> 2012
-> 2112
-> 2014
-> 2214
-> 2314
-> 2116
-> 2216
-> 2316
-> 2218
-> 2318
-> 2418
-> 2220
-> 2320
-> 2420
-> 2222
-> 2322
-> 2422
-> 2024
-> 2124
-> 2224
-> 1726
-> 1826
-> 1926
-> 1528
-> 1628
-> 1728
-> END DATA.
Preceding task required .02 seconds CPU time; .17 seconds elapsed.
-> set width=80 .
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 2
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
-> REGRESSION DESCRIPTIVES/
-> VARIABLES=Y,X,X2,X3/
-> STATISTICS=R,ANOVA,COEFF,CHA/
-> DEPENDENT=Y/ENTER X/
-> SCATTERPLOT SIZE (SMALL) (Y,X) (*RESID,X) (*RESID,*PRED)/
-> DEPENDENT=Y/ENTER X/ENTER X2/ENTER X3/
-> SCATTERPLOT SIZE(SMALL) (*RESID,X) (*RESID,*PRED) /
-> DEPENDENT=Y/ENTER X X2/
-> SCATTERPLOT SIZE(SMALL) (*RESID,X) (*RESID,*PRED).
There are 522,360 bytes of memory available.
The largest contiguous area has 519,888 bytes.
1964 bytes of memory required for REGRESSION procedure.
1936 more bytes may be needed for Residuals plots.
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 3
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Listwise Deletion of Missing Data
Mean Std Devi Label
Y 17.698 5.841
X 14.698 8.302
X2 283.349 252.448
X3 6153.674 6964.894
N of Cases = 43
Correlation:
Y X X2 X3
Y 1.000 .638 .446 .309
X .638 1.000 .972 .922
X2 .446 .972 1.000 .986
X3 .309 .922 .986 1.000
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 4
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 1 Dependent Variable.. Y
Descriptive Statistics are printed on Page 3
Block Number 1. Method: Enter X
Variable(s) Entered on Step Number
1.. X
Multiple R .63778
R Square .40676 R Square Change .40676
Adjusted R Square .39229 F Change 28.11203
Standard Error 4.55362 Signif F Change .0000
Analysis of Variance
DF Sum of Squares Mean Square
Regression 1 582.91592 582.91592
Residual 41 850.15385 20.73546
F = 28.11203 Signif F = .0000
------------------ Variables in the Equation ------------------
Variable B SE B Beta T Sig T
X .448718 .084631 .637778 5.302 .0000
(Constant) 11.102564 1.424584 7.794 .0000
End Block Number 1 All requested variables entered.
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 5
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 1 Dependent Variable.. Y
Residuals Statistics:
Min Max Mean Std Dev N
*PRED 12.0000 23.6667 17.6977 3.7254 43
*RESID -9.0000 6.3077 .0000 4.4991 43
*ZPRED -1.5294 1.6022 .0000 1.0000 43
*ZRESID -1.9764 1.3852 .0000 .9880 43
Total Cases = 43
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 6
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
Standardized Scatterplot
Across - X Down - Y
Out ++-----+-----+-----+-----+-----+-----++
3 + + Symbols:
| |
| | Max N
2 + +
| | . 1.0
| | : 2.0
1 + . .: :: +
| . .. :. .. : |
| ::. .. |
0 + . . : . +
| .. : |
| : |
-1 + +
| : |
| . |
-2 + . +
| : |
| . |
-3 + +
Out ++-----+-----+-----+-----+-----+-----++
-3 -2 -1 0 1 2 3 Out
Standardized Scatterplot
Across - X Down - *RESID
Out ++-----+-----+-----+-----+-----+-----++
3 + + Symbols:
| |
| | Max N
2 + +
| | . 1.0
| . . | : 2.0
1 + ... .: . +
| . ::. :. .. |
| .. .: |
0 + . . +
| . : |
| : . |
-1 + . +
| .. . . |
| : . |
-2 + . . +
| |
| |
-3 + +
Out ++-----+-----+-----+-----+-----+-----++
-3 -2 -1 0 1 2 3 Out
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 7
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
Standardized Scatterplot
Across - *PRED Down - *RESID
Out ++-----+-----+-----+-----+-----+-----++
3 + + Symbols:
| |
| | Max N
2 + +
| | . 1.0
| . . | : 2.0
1 + ... .: . +
| . ::. :. .. |
| .. .: |
0 + . . +
| . : |
| : . |
-1 + . +
| .. . . |
| : . |
-2 + . . +
| |
| |
-3 + +
Out ++-----+-----+-----+-----+-----+-----++
-3 -2 -1 0 1 2 3 Out
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 8
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 2 Dependent Variable.. Y
Descriptive Statistics are printed on Page 3
Block Number 1. Method: Enter X
Variable(s) Entered on Step Number
1.. X
Multiple R .63778
R Square .40676 R Square Change .40676
Adjusted R Square .39229 F Change 28.11203
Standard Error 4.55362 Signif F Change .0000
Analysis of Variance
DF Sum of Squares Mean Square
Regression 1 582.91592 582.91592
Residual 41 850.15385 20.73546
F = 28.11203 Signif F = .0000
------------------ Variables in the Equation ------------------
Variable B SE B Beta T Sig T
X .448718 .084631 .637778 5.302 .0000
(Constant) 11.102564 1.424584 7.794 .0000
End Block Number 1 All requested variables entered.
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 9
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 2 Dependent Variable.. Y
Block Number 2. Method: Enter X2
Variable(s) Entered on Step Number
2.. X2
Multiple R .97402
R Square .94871 R Square Change .54195
Adjusted R Square .94615 F Change 422.66795
Standard Error 1.35555 Signif F Change .0000
Analysis of Variance
DF Sum of Squares Mean Square
Regression 2 1359.56964 679.78482
Residual 40 73.50013 1.83750
F = 369.95027 Signif F = .0000
------------------ Variables in the Equation ------------------
Variable B SE B Beta T Sig T
X 2.576439 .106516 3.661978 24.188 .0000
X2 -.072019 .003503 -3.112514 -20.559 .0000
(Constant) .236528 .677634 .349 .7289
End Block Number 2 All requested variables entered.
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 10
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 2 Dependent Variable.. Y
Block Number 3. Method: Enter X3
Variable(s) Entered on Step Number
3.. X3
Multiple R .97457
R Square .94980 R Square Change .00109
Adjusted R Square .94593 F Change .84287
Standard Error 1.35822 Signif F Change .3642
Analysis of Variance
DF Sum of Squares Mean Square
Regression 3 1361.12452 453.70817
Residual 39 71.94524 1.84475
F = 245.94564 Signif F = .0000
------------------ Variables in the Equation ------------------
Variable B SE B Beta T Sig T
X 2.829993 .296083 4.022363 9.558 .0000
X2 -.092834 .022942 -4.012083 -4.046 .0002
X3 4.67108E-04 5.0879E-04 .556958 .918 .3642
(Constant) -.466721 1.023599 -.456 .6509
End Block Number 3 All requested variables entered.
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 11
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 2 Dependent Variable.. Y
Residuals Statistics:
Min Max Mean Std Dev N
*PRED 4.8257 23.1192 17.6977 5.6928 43
*RESID -2.3978 4.5290 .0000 1.3088 43
*ZPRED -2.2611 .9523 .0000 1.0000 43
*ZRESID -1.7654 3.3345 .0000 .9636 43
Total Cases = 43
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 12
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
Standardized Scatterplot
Across - X Down - *RESID
Out ++-----+----- . ---+-----+-----+-----++
3 + + Symbols:
| |
| | Max N
2 + +
| . | . 1.0
| . | : 2.0
1 + . .. . +
| . . . . . |
| : . . .. |
0 + . .. .. . +
| .. . .. . |
| . .. .. . |
-1 + . . +
| . . . |
| . . |
-2 + +
| |
| |
-3 + +
Out ++-----+-----+-----+-----+-----+-----++
-3 -2 -1 0 1 2 3 Out
Standardized Scatterplot
Across - *PRED Down - *RESID
Out ++-----+-----+--- . -----+-----+-----++
3 + + Symbols:
| |
| | Max N
2 + +
| . | . 1.0
| . | : 2.0
1 + . ... +
| . . . .. |
| : . . . . |
0 + . . .. : +
| . .. . . . |
| . . . .: |
-1 + . . +
| . . . |
| . . |
-2 + +
| |
| |
-3 + +
Out ++-----+-----+-----+-----+-----+-----++
-3 -2 -1 0 1 2 3 Out
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 13
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 3 Dependent Variable.. Y
Descriptive Statistics are printed on Page 3
Block Number 1. Method: Enter X X2
Variable(s) Entered on Step Number
1.. X2
2.. X
Multiple R .97402
R Square .94871 R Square Change .94871
Adjusted R Square .94615 F Change 369.95027
Standard Error 1.35555 Signif F Change .0000
Analysis of Variance
DF Sum of Squares Mean Square
Regression 2 1359.56964 679.78482
Residual 40 73.50013 1.83750
F = 369.95027 Signif F = .0000
------------------ Variables in the Equation ------------------
Variable B SE B Beta T Sig T
X2 -.072019 .003503 -3.112514 -20.559 .0000
X 2.576439 .106516 3.661978 24.188 .0000
(Constant) .236528 .677634 .349 .7289
End Block Number 1 All requested variables entered.
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 14
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 3 Dependent Variable.. Y
Residuals Statistics:
Min Max Mean Std Dev N
*PRED 5.1013 23.2783 17.6977 5.6895 43
*RESID -2.3900 4.7612 .0000 1.3229 43
*ZPRED -2.2140 .9809 .0000 1.0000 43
*ZRESID -1.7631 3.5124 .0000 .9759 43
Total Cases = 43
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 15
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
Standardized Scatterplot
Across - X Down - *RESID
Out ++-----+----- . ---+-----+-----+-----++
3 + + Symbols:
| |
| | Max N
2 + +
| | . 1.0
| . . | : 2.0
1 + . . +
| . .. . . .. . |
| : .. |
0 + . . ... . .. . +
| . . .. |
| . .. . . . |
-1 + . . +
| . . |
| .. . |
-2 + +
| |
| |
-3 + +
Out ++-----+-----+-----+-----+-----+-----++
-3 -2 -1 0 1 2 3 Out
Standardized Scatterplot
Across - *PRED Down - *RESID
Out ++-----+-----+-- . +-----+-----+-----++
3 + + Symbols:
| |
| | Max N
2 + +
| | . 1.0
| . . | : 2.0
1 + . . +
| . . : :: |
| : . . |
0 + . . . . . :: +
| . . . . |
| . . . . : |
-1 + . . +
| . . |
| . . . |
-2 + +
| |
| |
-3 + +
Out ++-----+-----+-----+-----+-----+-----++
-3 -2 -1 0 1 2 3 Out
17 Feb 98 CURVILINEAR REGRESSION--POLYNOMIAL EQUATION Page 16
16:12:30 sigma.oac.ucla.edu IBM RS/6000 IBM AIX 3.2.
Preceding task required .04 seconds CPU time; .10 seconds elapsed.
--========================_48736590==_
Content-Type: text/plain; name="curve.sps"; charset="us-ascii"
Content-Disposition: attachment; filename="curve.sps"
TITLE CURVILINEAR REGRESSION--POLYNOMIAL EQUATION.
DATA LIST RECORDS=1
/Y 1-2 X 3-4.
COMPUTE X2=X**2.
COMPUTE X3=X**3.
BEGIN DATA
3 2
4 2
6 2
5 2
7 4
10 4
10 4
13 6
14 6
15 6
16 8
17 8
21 8
1810
1910
2010
1912
2012
2112
2014
2214
2314
2116
2216
2316
2218
2318
2418
2220
2320
2420
2222
2322
2422
2024
2124
2224
1726
1826
1926
1528
1628
1728
END DATA.
set width=80 .
REGRESSION DESCRIPTIVES/
VARIABLES=Y,X,X2,X3/
STATISTICS=R,ANOVA,COEFF,CHA/
DEPENDENT=Y/ENTER X/
SCATTERPLOT SIZE (SMALL) (Y,X) (*RESID,X) (*RESID,*PRED)/
DEPENDENT=Y/ENTER X/ENTER X2/ENTER X3/
SCATTERPLOT SIZE(SMALL) (*RESID,X) (*RESID,*PRED) /
DEPENDENT=Y/ENTER X X2/
SCATTERPLOT SIZE(SMALL) (*RESID,X) (*RESID,*PRED).