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Independent variables. The equation of the fitted model is
P = 0,0575519*LAG(Y;1) - 0,187027*LAG(M;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 97,3609% of the variability in P. The adjusted R-squared
statistic, which is more suitable for comparing models with different
numbers of independent variables, is 97,2632%. (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 15,9338.
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 12,7997 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
LAG(M;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 P.5
-----------------------------------------------------------------------------
Dependent variable: P
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
LAG(Y;1) 0,0134573 0,00658934 2,04229 0,0518
LAG(M;1) 0,120143 0,0484885 2,47776 0,0203
W -13,631 1,68329 -8,09784 0,0000
G 0,224049 0,0358359 6,25209 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 258168,0 4 64542,0 1022,70 0,0000
Residual 1577,74 25 63,1095
-----------------------------------------------------------------------------
Total 259746,0 29
R-squared = 99,3926 percent
R-squared (adjusted for d.f.) = 99,3197 percent
Standard Error of Est. = 7,94415
Mean absolute error = 6,00654
Durbin-Watson statistic = 1,17007
The StatAdvisor
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The output shows the results of fitting a multiple linear
regression model to describe the relationship between P and 4