Independent variables. The equation of the fitted model is

L = 64,9814*Ppr/LAG(Ppr;1) + 1,81746*time

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 99,9619% of the variability in L. The adjusted R-squared

statistic, which is more suitable for comparing models with different

numbers of independent variables, is 99,9603%. (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 2,04674.

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 1,70969 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 0,0000, belonging to

Ppr/LAG(Ppr;1). Since the P-value is less than 0.01, the highest

order term is statistically significant at the 99% confidence level.

Consequently, you probably don't want to remove any variables from the

model.

Multiple Regression Analysis 2MNK2.I

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

Dependent variable: I

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

Standard T

Parameter Estimate Error Statistic P-Value

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

Tr -338,478 343,519 -0,985323 0,3352

Kpr 1,11596 0,300717 3,71098 0,0012

LAG(Kpr;1) -1,1007 0,30979 -3,55306 0,0018

Ypr -0,041105 0,132623 -0,309938 0,7595

LAG(Ypr;1) 0,132053 0,151904 0,869321 0,3941

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

Analysis of Variance

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

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

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

Model 9,78428E6 5 1,95686E6 382,67 0,0000

Residual 112500,0 22 5113,65

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

Total 9,89678E6 27

R-squared = 98,8633 percent

R-squared (adjusted for d.f.) = 98,6566 percent

Standard Error of Est. = 71,5098

Mean absolute error = 52,7116

Durbin-Watson statistic = 2,05003

The StatAdvisor

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The output shows the results of fitting a multiple linear

regression model to describe the relationship between I and 5