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This monograph presents a comprehensive and up-to-date account of the developments in optimality aspects of crossover designs. Crossover designs are immensely useful in various areas of human investigation including agriculture, animal nutrition, clinical trials, pharmaceutical studies, biological assays, weather modification experiments, sensory evaluation of food products and learning experiments. Research on the optimality aspects of crossover designs has developed only in the last three decades, and it has now emerged as a potential field for further investigation. This book is the first c

Experimental design. --- Optimal designs (Statistics)

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Experimental design --- Psychology, Experimental --- Psychology --- Research

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Replication in experimental economics' highlights the importance of replicating previous economic experiments for understanding the robustness and generalizability of behavior. Replication enables experimental findings to be subjected to rigorous scrutiny. Despite this obvious advantage, direct replication remains relatively scant in economics. One possible explanation for this situation is that publication outlets favor novel work over tests of robustness. This volume of Research in experimental economics raises awareness of the need for replication by being the first collection of papers specifically dedicated to the replication of previously published work. The chapters, by leading researchers in the field, explore the robustness of topics from the effects of subsidizing charitable giving to people's ability to backwards induct and from the impact of social history on trust to the role of isolation on valuation. Readers will gain a better understanding of the role that replication plays in scientific discovery as well as valuable insights into the robustness of previously reported findings.

Experimental economics. --- Replication (Experimental design) --- Experimental design --- Economics --- Methodology --- Experimental economics --- E-books --- Business & Economics --- Econometrics.

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This third edition of Design of Experiments for Engineers and Scientists adds to the tried and trusted tools that were successful in so many engineering organizations with new coverage of design of experiments (DoE) in the service sector. Case studies are updated throughout, and new ones are added on dentistry, higher education, and utilities. Although many books have been written on DoE for statisticians, this book overcomes the challenges a wider audience faces in using statistics by using easy-to-read graphical tools. Readers will find the concepts in this book both familiar and easy to understand, and users will soon be able to apply them in their work or research. This classic book is essential reading for engineers and scientists from all disciplines tackling all kinds of product and process quality problems and will be an ideal resource for students of this topic.

Experimental design. --- Research, Industrial. --- Plan d'expérience. --- Recherche industrielle. --- Experimental design --- Research, Industrial --- Scientific research.

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Principles of Experimentation: Designing Experiments and Analyzing Their Results introduces the basic concepts of experimentation as the rational use of experimental designs. This book covers the design of such plans as well as the analysis and interpretation of the results obtained. These concepts are presented in a very general manner and are illustrated with numerous examples. The set also includes numerical tables, a bibliographic index of more than 400 references, an index of English translations and a subject index. Additional information is available on a website. This book is intended for teachers, students and researchers in all disciplines who use the experimental method in universities, colleges and public and private research centers. It complements the books Statistical Theory and Methods: Agronomic Applications (2 vols.), originally published in 1969 and 1970, and Theoretical and Applied Statistics (2 vols.), (1998 and subsequent editions).

Experimental design. --- Mathematical optimization. --- Agriculture --- Research --- Statistical methods.