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