Design of Experiments

This textbook presents the basic concepts of linear models, design and analysis of experiments. With the rigorous treatment of topics and provision of detailed proofs, this book aims at bridging the gap between basic and advanced topics of the subject. Initial chapters of the book explain linear estimation in linear models and testing of linear hypotheses, and the later chapters apply this theory to the analysis of specific models in designing statistical experiments.

With Real Time Case Study and Case Method

DoE Using Minitab: From Basics to Plackett-Burman, Full/Fractional Factorial, Response Surface (CCD) Designs

Factorial Designs | Fractional Factorial Designs | Taguchi Designs - Lean Six Sigma Black Belt Level

Mixture Designs to Optimize Formulations Using R: Simplex Lattice Designs, Simplex Centroid Designs, D-Optimal Designs.

Throughout the book, the design and analysis of experiments are conducted involving several approaches, namely, Taguchi, response surface methods, statistical correlations, or even fractional factorial and model-based evolutionary operation designs. This book not only presents a theoretical overview about the different approaches but also contains material that covers the use of the experimental analysis applied to several chemical processes.

DoE using R: Response Surface Methodology, Lack-of-Fit, Central Composite Designs, Box-Behnken Designs