Independent variables. The equation of the fitted model is

U = 21,5722 + 0,0013923*Y - 1,53967*W - 0,0813094*P + 0,462716*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 92,0207% of the variability in U. The adjusted R-squared

statistic, which is more suitable for comparing models with different

numbers of independent variables, is 90,7441%. The standard error of

the estimate shows the standard deviation of the residuals to be

0,393726. 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 0,279029 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 0,0012, belonging to

Y. 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 M.1

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

Dependent variable: M

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

Standard T

Parameter Estimate Error Statistic P-Value

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

CONSTANT 492,7 9,44851 52,1458 0,0000

Y*P 0,000307758 0,0000169264 18,1821 0,0000

Irr -0,918023 1,0049 -0,913552 0,3690

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

Analysis of Variance

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

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

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

Model 171600,0 2 85800,0 174,71 0,0000

Residual 13259,5 27 491,091

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

Total (Corr.) 184859,0 29

R-squared = 92,8273 percent

R-squared (adjusted for d.f.) = 92,296 percent

Standard Error of Est. = 22,1606

Mean absolute error = 17,7718

Durbin-Watson statistic = 0,877621

The StatAdvisor

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

The output shows the results of fitting a multiple linear

regression model to describe the relationship between M and 2