Abstract
This text presents fundamentals and a critical evaluation of the chemometric techniques utilized for the multivariate optimization of analytical methods. Firstly, a description of the two-level full factorial design is done. The linear model, effect calculation, statistical significance of the effects, curvature test, Pareto charts and others issues of this chemometric tool are discussed. Also, characteristics of the surface response methodologies (SRM): Box Behnken design, Doehlert matrix, central composite, and three factorial designs are summarized and compared. Remarks about quadratic models, description of the application and need of the multiple response functions employed in experimental designs, efficiencies of the SRM's and robustness tests are also discussed. A glossary with chemometric terms is also presented.
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