Design and Analysis of Experiments

Angela Dean, Daniel Voss, Danel Draguljić (Autoren)

Buch | Softcover

XXV, 840 Seiten

2017 | 2nd ed. 2017
Springer International Publishing (Verlag)
978-3-319-52248-7 (ISBN)

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This textbook takes a strategic approach to the broad-reaching subject of experimental design by identifying the objectives behind an experiment and teaching practical considerations that govern design and implementation, concepts that serve as the basis for the analytical techniques covered. Rather than a collection of miscellaneous approaches, chapters build on the planning, running, and analyzing of simple experiments in an approach that results from decades of teaching the subject. In most experiments, the procedures can be reproduced by readers, thus giving them a broad exposure to experiments that are simple enough to be followed through their entire course. Outlines of student and published experiments appear throughout the text and as exercises at the end of the chapters. The authors develop the theory of estimable functions and analysis of variance with detail, but at a mathematical level that is simultaneously approachable. Throughout the book, statistical aspects of analysiscomplement practical aspects of design.

This new, second edition includes

an additional chapter on computer experiments
additional "Using R" sections at the end of each chapter to illustrate R code and output
updated output for all SAS programs and use of SAS Proc Mixed
new material on screening experiments and analysis of mixed models

Angela Dean, PhD, is Professor Emeritus of Statistics and a member of the Emeritus Academy at The Ohio State University, Columbus, Ohio. She is a fellow of the American Statistical Association and the Institute of Mathematical Statistics, and a former chair of the Section on Physical and Engineering Sciences of the American Statistical Association. Her research interests include design of screening and computer experiments.Daniel Voss, PhD, is Professor Emeritus of Mathematics and Statistics at Wright State University, Dayton, Ohio. He is a former Interim Dean of the College of Science and Mathematics and Interim Director of the Statistical Consulting Center at WSU. His research interests include the analysis of saturated fractional factorial experiments, and the equivalence of hypothesis testing and confidence interval estimation.Danel Draguljic, PhD, is Assistant Professor of Mathematics at Franklin & Marshall College, Lancaster, Pennsylvania. His research interests include design of screening experiments, design of computer experiments, and statistics education.

Principles and Techniques.- Planning Experiments.- Designs With One Source of Variation.- Inferences for Contrasts and Treatment Means.- Checking Model Assumptions.- Experiments With Two Crossed Treatment Factors.- Several Crossed Treatment Factors.- Polynomial Regression.- Analysis of Covariance.- Complete Block Designs.- Incomplete Block Designs.- Designs With Two Blocking Factors.- Confounded Two-Level Factorial Experiments.- Confounding in General Factorial Experiments.- Fractional Factorial Experiments.- Response Surface Methodology.- Random Effects and Variance Components.- Nested Models.- Split-Plot Designs

"The textbook provides a practically oriented version of design and analysis of experiments. The corresponding methods are illustrated by means of numerous simple experiments. Thus, the models and methods are equipped with many examples, exercises, numerical results and related tables and figures. ... The present volume can be recommended as textbook for lectures on models and methods of experimental design as well as handbook for use in practice." (Kurt Marti, zbMATH 1383.62001, 2018)

Erscheinungsdatum	08.03.2017
Reihe/Serie	Springer Texts in Statistics
Zusatzinfo	XXV, 840 p. 146 illus., 52 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	178 x 254 mm
Themenwelt	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
Themenwelt	Naturwissenschaften ► Physik / Astronomie
Schlagworte	Analysis of covariance • Analysis of Experiments • blocking factors • Design of Experiments • Experiment • Factorial experiments • Fitting models • Inference for Contrasts • mathematics and statistics • Planning experiments • Polynomial Regression • probability and statistics • Probability theory and stochastic processes • random effects • Science: general issues • Statistical Theory and Methods • Statistics for Engineering, Physics, Computer Scie • stochastics • Variation
ISBN-10	3-319-52248-5 / 3319522485
ISBN-13	978-3-319-52248-7 / 9783319522487
Zustand	Neuware