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The R-Squared statistic indicates that the model as fitted
explains 87,1869% of the variability in M. The adjusted R-squared
statistic, which is more suitable for comparing models with different
numbers of independent variables, is 86,7293%. (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 219,466.
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 168,824 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 0,0000, belonging to
Irr. 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.3
-----------------------------------------------------------------------------
Dependent variable: M
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Y 0,164489 0,00445718 36,9042 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 1,03059E7 1 1,03059E7 1361,92 0,0000
Residual 219449,0 29 7567,21
-----------------------------------------------------------------------------
Total 1,05254E7 30
R-squared = 97,915 percent
R-squared (adjusted for d.f.) = 97,915 percent
Standard Error of Est. = 86,9897
Mean absolute error = 65,1479
Durbin-Watson statistic = 0,0701086
The StatAdvisor
---------------
The output shows the results of fitting a multiple linear
regression model to describe the relationship between M and 1
Independent variables. The equation of the fitted model is
M = 0,164489*Y
Since the P-value in the ANOVA table is less than 0.01, there is a
statistically significant relationship between the variables at the