Independent variables. The equation of the fitted model is

I = 0,0169738*C + 0,968835*K - 0,917308*LAG(K;1)

Since the P-value in the ANOVA table is less than 0.01, there is a

statistically significant relationship between the variables at the

99% Confidence level.

The R-Squared statistic indicates that the model as fitted

explains 99,9912% of the variability in I. The adjusted R-squared

statistic, which is more suitable for comparing models with different

numbers of independent variables, is 99,9905%. (Note: since the model

does not contain a constant, you should be careful in interpreting the

R-Squared values. Do not compare these R-Squared values with those of

models which do contain a constant.) The standard error of the

estimate shows the standard deviation of the residuals to be 5,85637.

This value can be used to construct prediction limits for new

observations by selecting the Reports option from the text menu. The

mean absolute error (MAE) of 4,28823 is the average value of the

residuals. The Durbin-Watson (DW) statistic tests the residuals to

determine if there is any significant correlation based on the order

in which they occur in your data file. Since the DW value is greater

than 1.4, there is probably not any serious autocorrelation in the

residuals.

In determining whether the model can be simplified, notice that the

highest P-value on the independent variables is 0,0742, belonging to

C. Since the P-value is less than 0.10, that term is statistically

significant at the 90% confidence level. Depending on the confidence

level at which you wish to work, you may or may not decide to remove C

from the model.

Multiple Regression Analysis C.1

-----------------------------------------------------------------------------

Dependent variable: C

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Standard T

Parameter Estimate Error Statistic P-Value

-----------------------------------------------------------------------------

Y 0,702285 0,0284598 24,6764 0,0000

G -0,306518 0,14261 -2,14934 0,0404

-----------------------------------------------------------------------------

Analysis of Variance

-----------------------------------------------------------------------------

Source Sum of Squares Df Mean Square F-Ratio P-Value

-----------------------------------------------------------------------------

Model 1,56665E8 2 7,83323E7 40708,30 0,0000

Residual 53878,5 28 1924,23

-----------------------------------------------------------------------------

Total 1,56718E8 30

R-squared = 99,9656 percent

R-squared (adjusted for d.f.) = 99,9644 percent

Standard Error of Est. = 43,8661

Mean absolute error = 37,5121

Durbin-Watson statistic = 1,41432

The StatAdvisor

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The output shows the results of fitting a multiple linear

regression model to describe the relationship between C and 2