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A high determination coefficient R2 of 99.3% was obtained.
The model had a high determination coefficient (R2 = 0.92) and low lack of fit (Table 1).
All the regression models yielded a good fit with high determination coefficient and F value.
The checking of fitting goodness of improved interaction parameter C value shows a high determination coefficient.
The quadratic model obtained fits well to predict the response with a high determination coefficient of R2 (0.995).
The high determination coefficient (R2 = 98.98%) and the low probability value (Pr < 0.0001) proved that the model matched the experimental data, and had a high predictive ability.
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The corresponding parameters were estimated by multiple linear regression (MLR) and high determination coefficients (higher than 0.98) were obtained.
The three regression models performed to evaluate the predictive validity showed high determination coefficients (78,2 %. 94,9 % and 75,4 %).
In contrast to the monocarboxylic acids, the sorption functions of the dicarboxylic acids could be fitted by the two-site Langmuir approach, resulting in high determination coefficients.
Both proposed linear models MLR exhibit high determination coefficients, good stabilities and prediction abilities, using only three descriptors for each model.
All the multivariate regression models revealed high determination coefficients for three parameters, among which the response surface regression model yielded the highest values.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com