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reduction F test diesel

R Software Module: esteq.wasp (opens new window with default values)
Title produced by software: Estimate Equation
Date of computation: Sun, 16 Dec 2007 06:50:25 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Dec/16/t1197812094ucz2t967wn6b47b.htm/, Retrieved Sun, 16 Dec 2007 14:34:54 +0100
 
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Dataseries X:
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36429 0.77632 32720 0.80364 34490 0.83065 34749 0.76103 30945 0.72187 34302 0.72929 30400 0.73339 25543 0.75884 32188 0.75423 34395 0.77581 27148 0.77753 26634 0.77016 34257 0.76800 34794 0.76352 38927 0.80984 38512 0.83697 33325 0.86371 40658 0.85027 32719 0.86945 29323 0.92155 34384 0.93647 35153 0.98323 30937 0.95760 28079 0.93332 39703 0.90135 35245 0.92446 41324 0.98061 40802 1.01953 37732 1.00784 41527 1.07107 33441 1.09458 32885 1.10923 36804 1.12907 35593 1.12374 34355 1.07400 27045 1.04497 45587 1.06290 40370 1.06646 48209 1.08848 40275 1.11763 36760 1.10842 42588 1.10560 35365 1.11306 33014 1.11039 36944 1.05590 35649 1.03703 34814 1.04327 26041 1.03839 45636 0.99784 40040 1.01526 47725 1.05461 40263 1.08300 43339 1.08503 47283 1.09953 40492 1.11442 35768 1.10371 28539 1.13018 42971 1.15868 36144 1.24067 26950 1.21680
 
Text written by user:
 
Output produced by software:
This free online calculator computes equations with the following options: constant, linear deterministic trend, first differences, hyperbolic, exponential, geometric, quadratic, cubic, quartic, seasonal dummies, predetermination (lagged endogenous variables), Ordinary Least Squares, Bootstrap, Jackknife.

Econometric Regression Equation

Multiple Linear Regression - Estimated Regression Equation
inschrijv[t] = +3434.39554468 prijs[t] +29858.077965917 +90.781511989003 t^1 + e[t]

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
prijs[t]3434.39554511089.5619540.3096960.7579210.378961
Constant29858.0779668385.4750593.560690.0007550.000377
t^190.78151291.6807320.9901920.3262650.163133
VariableElasticityS.E.*T-STAT
H0: |elast| = 1
2-tail p-value1-tail p-value
%prijs[t]0.0929550.300148-3.0219890.0037570.001879
%Constant0.830070.233121-0.7289360.4690260.234513
%t^10.0769750.077738-11.87360500
VariableStand. Coeff.S.E.*T-STAT
H0: coeff = 0
2-tail p-value1-tail p-value
S-prijs[t]0.0889160.2871060.3096960.7579210.378961
S-Constant00010.5
S-t^10.284290.2871060.9901920.3262650.163133
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
prijs[t]0.040986
Constant0.426565
t^10.13004
Critical Values (alpha = 5%)
1-tail CV at 5%1.68
2-tail CV at 5%2

Multiple Linear Regression - Regression Statistics
Multiple R0.36659
R-squared0.134388
Adjusted R-squared0.104016
F-TEST4.424689
Observations60
Degrees of Freedom57
Multiple Linear Regression - Residual Statistics
Standard Error5296.388498
Sum Squared Errors1598948673.6383
Log Likelihood-598.08434
Durbin-Watson1.60404
Von Neumann Ratio1.631227
# e[t] > 029
# e[t] < 031
# Runs26
Stand. Normal Runs Statistic-1.294859

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error29454317.672285
Akaike (1973) Log Information Criterion17.198268
Akaike (1974) Information Criterion29451859.560012
Schwarz (1978) Log Criterion17.302985
Schwarz (1978) Criterion32703244.042323
Craven-Wahba (1979) Generalized Cross Validation29528138.017329
Hannan-Quinn (1979) Criterion30683274.933514
Rice (1984) Criterion29610160.622932
Shibata (1981) Criterion29314059.016703

Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression2248240377.21165124120188.60583
Residual571598948673.638328051731.116462
Total591847189050.8531308288.997458
F-TEST4.424689
p-value0.016357





 
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Software written by Ed van Stee & Patrick Wessa


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