Theory of Factorial Experiments

This book introduces modern methods for estimating and analysing factorial experiments, including a new Hadamard matrix-based technique for 2n designs. It covers confounded, asymmetrical, and supersaturated designs and demonstrates the use of factorial experiments in constructing various block designs. Practical RStudio implementations are included. The book also explores the analysis of variance for asymmetrical factorial designs and confounded experiments, including single and double-confounding schemes. It also offers a practical guide to implementing these methods in RStudio, including worked examples and computation of ANOVA tables.

Features:

• Introduces a novel method using Hadamard matrices to estimate effects and compute ANOVA tables in 2n factorial experiments

• Discusses estimation of effects in ternary symmetrical designs using linear and quadratic contrasts with single degrees of freedom

• Covers estimation techniques and ANOVA computation for asymmetrical factorial and confounded designs.

• Demonstrates the use of factorial experiments for constructing BIBDs, PBIBDs, and other complex experimental designs

• Offers practical R code and examples for estimating effects and generating ANOVA tables from real datasets

This book is for graduate students, academic researchers, and applied statisticians in agricultural, industrial, and experimental sciences who seek advanced yet accessible coverage of factorial experiments and their real-world applications.

Dilip Kumar Ghosh completed his Bachelor’s and Master’s degrees in Statistics from Bhagalpur University. He gained his Ph.D. in Statistics, specializing in Design of Experiments at ISI Delhi under M. N. Das. He has worked at CMFRI, Cochin; Tocklai Experimental Station, Jorhat; Saurashtra University, Rajkot from Lecturer to Professor and Head. He is the founder faculty of department of Statistics at Saurashtra University. After his retirement, UGC selected him as a BSR Faculty Fellow for three years. He has published 150 research papers in national and internationally reputed journals. He has more than 50 years of teaching and research experience. He supervised 43 Ph.D. students in Statistics, OR, Inference, and Management. He has been teaching Design of Experiments, including Factorial Experiments since the last 40 years. He visited West Florida University, USA, and University of Manitoba, Canada, as a research collaborator at least ten times and published papers along with them. Further, he participated in several international conferences abroad and has organized more than 15 conferences and two refresher courses. He is a member of more than 15 professional bodies, an Editorial board member in 10 journals and Editor in Chief of Gujarat Journal of Statistics and Data Science.

Dilip Kumar Ghosh completed his Bachelors and Master’s degree in Statistics from Bhagalpur University. He gained his Ph.D. in Statistics, specializing in Design of Experiments at ISI Delhi under M. N. Das. He has worked at CMFRI, Cochin; Tocklai Experimental Station, Jorhat; Saurashtra University Rajkot from Lecturer to Professor and Head. He is founder faculty of department of Statistics at Saurashtra University. After his retirement, UGC selected him as BSR Faculty Fellow for three years. He has published 150 research papers in national and international reputed journals. He has more than 50 years of teaching and research experience. He supervised 43 Ph.D. students in Statistics, OR, Inference, Management. He has been teaching Design of Experiments including Factorial Experiments since the last 40 years. He visited West Florida University, USA and University of Manitoba, Canada as a research collaborator at least ten times and published papers along with them. Further, he participated in several international conferences abroad and has organized more than 15 conferences and two refresher courses. He is a member of more than 15 professional bodies, Editorial board member in 10 journals and Editor in Chief of Gujarat Journal of Statistics and Data Science.