Independent variables. The equation of the fitted model is

W = 13,4472 + 0,0176211*P - 21,7858*Ur

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 79,0721% of the variability in W. The adjusted R-squared

statistic, which is more suitable for comparing models with different

numbers of independent variables, is 77,5219%. The standard error of

the estimate shows the standard deviation of the residuals to be

0,458067. 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 0,338887 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 less

than 1.4, there may be some indication of serial correlation. Plot

the residuals versus row order to see if there is any pattern which

can be seen.

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

highest P-value on the independent variables is 0,0307, belonging to

Ur. Since the P-value is less than 0.05, that term is statistically

significant at the 95% confidence level. Consequently, you probably

don't want to remove any variables from the model.

Multiple Regression Analysis W.2

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

Dependent variable: W

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

Standard T

Parameter Estimate Error Statistic P-Value

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

P 0,0455632 0,00707622 6,43892 0,0000

Ur 173,288 11,6535 14,87 0,0000

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

Analysis of Variance

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

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

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

Model 5553,24 2 2776,62 766,31 0,0000

Residual 101,454 28 3,62337

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

Total 5654,69 30

R-squared = 98,2058 percent

R-squared (adjusted for d.f.) = 98,1418 percent

Standard Error of Est. = 1,90352

Mean absolute error = 1,52481

Durbin-Watson statistic = 0,628284

The StatAdvisor

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

The output shows the results of fitting a multiple linear

regression model to describe the relationship between W and 2

Independent variables. The equation of the fitted model is

W = 0,0455632*P + 173,288*Ur

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

statistically significant relationship between the variables at the