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R Software Module: esteq.wasp (opens new window with default values)
Title produced by software: Estimate Equation
Date of computation: Mon, 12 Nov 2007 11:04:34 -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/Nov/12/t1194890388xn64kvspjsftmou.htm/, Retrieved Mon, 12 Nov 2007 18:59:48 +0100
 
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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
AvgTAT[t] = -0.19980152874623 Low[t] +0.15099193324836 Medium[t] +0.32203702772875 High[t] +7.4110743774507 + e[t]

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
Low[t]-0.1998020.362493-0.5511870.6014120.300706
Medium[t]0.1509920.2863790.5272450.6169410.30847
High[t]0.3220370.3292560.9780730.3658110.182905
Constant7.4110747.7596180.9550820.3764160.188208
VariableElasticityS.E.*T-STAT
H0: |elast| = 1
2-tail p-value1-tail p-value
%Low[t]-0.0496240.090031-10.5560944.3E-052.1E-05
%Medium[t]0.1253330.237713-3.6795030.0103370.005168
%High[t]0.4399070.449769-1.2452920.2594510.129726
%Constant0.4843840.507165-1.0166640.3485430.174271
VariableStand. Coeff.S.E.*T-STAT
H0: coeff = 0
2-tail p-value1-tail p-value
S-Low[t]-0.2211990.401314-0.5511870.6014120.300706
S-Medium[t]0.1975970.3747730.5272450.6169410.30847
S-High[t]0.3936320.4024560.9780730.3658110.182905
S-Constant00010.5
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
Low[t]-0.219532
Medium[t]0.210427
High[t]0.370828
Constant0.363273
Critical Values (alpha = 5%)
1-tail CV at 5%1.95
2-tail CV at 5%2.45

Multiple Linear Regression - Regression Statistics
Multiple R0.406314
R-squared0.165091
F-TEST0.39547
Observations10
Degrees of Freedom6
Multiple Linear Regression - Residual Statistics
Standard Error2.420388
Sum Squared Errors35.14968
Log Likelihood-20.474537
Durbin-Watson2.944651
Von Neumann Ratio3.271835
# e[t] > 04
# e[t] < 06
# Runs8
Runs Statistic1.545367

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error8.201592
Akaike (1973) Log Information Criterion2.05703
Akaike (1974) Information Criterion7.822705
Schwarz (1978) Log Criterion2.178064
Schwarz (1978) Criterion8.8292
Craven-Wahba (1979) Generalized Cross Validation9.7638
Hannan-Quinn (1979) Criterion6.850053
Rice (1984) Criterion17.57484
Shibata (1981) Criterion6.326942

Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression36.950322.316773
Residual635.149685.85828
Total942.14.6777777777778
F-TEST0.39547
p-value0.761242




 
Charts produced by software:
 
Parameters:
 
R code (references can be found in the software module):
 





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Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


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