Environmental Engineering Reference
In-Depth Information
Table 23. Model summary statistics for response density
r 2
Adjusted r 2
Predicted r 2
Source
Std.
Dev
Press
Linear
0.072
0.7744
0.7334
0.6004
0.10
Quadratic
0.025
0.9796
0.9669
0.9256
0.019
Special Cubic
0.027
0.9799
0.9628
0.8776
0.031
Cubic
0.029
0.9869
0.9576
Table 24. Model summary statistics for response cadmium leaching
Source
Std.
Dev.
Adjusted
R-Squared
Predicted
R-quared
R-Squared
Press
Linear
0.080
0.8550
0.8286
0.7854
0.10
Suggested
Quadratic
0.066
0.9281
0.8831
0.8383
0.078
Special
Cubic
0.071
0.9282
0.8667
0.7601
0.12
Cubic
5.545E-
003
0.9997
0.9992
Suggested
Table 25. Model summary statistics for response lead leaching
Source
Std.
Dev.
Adjusted
R-Squared
Predicted
R-Squared
R-Squared Press
Linear
3.30
0.6752
0.6161
0.5042
182.54
Quadratic
1.82
0.9277
0.8825
0.8430
57.82
Suggested
Special
Cubic
1.78
0.9398
0.8882
0.7908
77.02
Cubic
0.069
0.9999
0.9998
Suggested
From Table 26 of ANOVA for mixture special cubic model for response
compressive strength Prob > F value implies the model is significant and there
is only a 0.01% chance that a "Model F-Value" this large could occur due to
noise. However. When "Prob > F" less than 0.05 indicate that the model terms
are significant. And values greater than 0.1 indicate the model terms are not
significant. In this study Linear Mixture Components, AB, AC, BC, ABC are
significant model terms. The analysis showed that the "Lack of Fit F-value" of
0.38 is not significant relative to the pure error and there is a 77.06% chance
that a "Lack of Fit F-value" this large could occur due to noise. For model
fitting, Non-significant lack of fit is good and desired one. For other response
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