The R-Squared and the Adjusted R-Squared correlation functions were used in this study to check the model adequacy. The coefficient of Determination (R-Squared) statistically expresses the explanatory power of the variables in the model. In Table 3.6, the Coefficient of Determination (R-Squared) of 0.9345 indicated that more than 93% of the experimental data explained the independent variables and thus described the model more explicitly. Adjusted R-Squared topples the R-Squared and adjusts the number of variables included in the response surface quadratic model, leading to higher accuracy and precision in describing the model. An Adjusted R-Squared of 0.8755 indicates that an addition of a new model term (or some more model terms) will improve the model by about 87% more likely than would be expected by chance. The Predicted R-Squared of 0.4980 was not close to the Adjusted R-Squared of 0.8755. The difference was more than 0.2 and this indicated large block effect in the response surface quadratic model. Adequacy Precision measures the signal to noise ratio. A ratio greater than 4 is desirable, therefore from Table 3.6, the ratio of 10.893 indicated an adequate signal and hence, this quadratic model could be used to navigate design space.
Table 3.7 Model Coefficients