Applications of Statistics to Industrial Experimentation
Applications of Statistics to Industrial Experimentation

Author: Cuthbert Daniel

Publisher: John Wiley & Sons

Published: 2009-09-25

Total Pages: 321

ISBN-13: 0470317175

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Other volumes in the Wiley Series in Probability and MathematicalStatistics, Ralph A. Bradley, J. Stuart Hunter, David G. Kendall,& Geoffrey S. Watson, Advisory Editors Statistical Models inApplied Science Karl V. Bury Of direct interest to engineers andapplied scientists, this book presents general principles ofstatistics and specific distribution methods and models. Prominentdistribution properties and methods that are useful over a widerange of applications are covered in detail. The strengths andweaknesses of the distributional models are fully described, givingthe reader a firm, intuitive approach to the selection of the modelmost appropriate to the problem at hand. 1975 656 pp. FittingEquations To Data Computer Analysis of Multifactor Data forScientists and Engineers Cuthbert Daniel & Fred S. Wood Withthe assistance of John W. Gorman The purpose of this book is tohelp the serious data analyst, scientist, or engineer with acomputer to: recognize the strengths and limitations of his data;test the assumptions implicit in the least squares methods used tofit the data; select appropriate forms of the variables; judgewhich combinations of variables are most influential; and state theconditions under which the fitted equations are applicable.Throughout, mathematics is kept at the level of college algebra.1971 342 pp. Methods for Statistical Analysis of Reliability AndLife Data Nancy R. Mann, Ray E. Schafer & Nozer D. SingpurwallaThis book introduces failure models commonly used in reliabilityanalysis, and presents the most useful methods for analyzing thelife data of these models. Highlights include: material onaccelerated life testing; a comprehensive treatment of estimationand hypothesis testing; a critical survey of methods forsystem-reliability confidence bonds; and methods for simulation oflife data and for testing fit. 1974 564 pp.

Design of Experiments for Engineers and Scientists
Design of Experiments for Engineers and Scientists

Author: Jiju Antony

Publisher: Elsevier

Published: 2014-02-22

Total Pages: 221

ISBN-13: 0080994199

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The tools and techniques used in Design of Experiments (DoE) have been proven successful in meeting the challenge of continuous improvement in many manufacturing organisations over the last two decades. However research has shown that application of this powerful technique in many companies is limited due to a lack of statistical knowledge required for its effective implementation.Although many books have been written on this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as through using statistical methods and readers will find the concepts in this book both familiar and easy to understand.This new edition includes a chapter on the role of DoE within Six Sigma methodology and also shows through the use of simple case studies its importance in the service industry. It is essential reading for engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic. - Written in non-statistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE - Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem solving methodology - New edition includes a full chapter on DoE for services as well as case studies illustrating its wider application in the service industry

Statistical Analysis of Designed Experiments
Statistical Analysis of Designed Experiments

Author: Ajit C. Tamhane

Publisher: John Wiley & Sons

Published: 2012-09-12

Total Pages: 724

ISBN-13: 1118491432

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A indispensable guide to understanding and designing modern experiments The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences. The book supplies a foundation for the subject, beginning with basic concepts of DOE and a review of elementary normal theory statistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in a comprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for its analysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesis tests. Numerous theoretical and applied exercises are provided in each chapter, and answers to selected exercises are included at the end of the book. An appendix features three case studies that illustrate the challenges often encountered in real-world experiments, such as randomization, unbalanced data, and outliers. Minitab® software is used to perform analyses throughout the book, and an accompanying FTP site houses additional exercises and data sets. With its breadth of real-world examples and accessible treatment of both theory and applications, Statistical Analysis of Designed Experiments is a valuable book for experimental design courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge of DOE.

Experiments
Experiments

Author: C. F. Jeff Wu

Publisher: John Wiley & Sons

Published: 2011-09-20

Total Pages: 562

ISBN-13: 1118211537

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Praise for the First Edition: "If you . . . want an up-to-date, definitive reference written by authors who have contributed much to this field, then this book is an essential addition to your library." —Journal of the American Statistical Association Fully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments, Second Edition introduces some of the newest discoveries—and sheds further light on existing ones—on the design and analysis of experiments and their applications in system optimization, robustness, and treatment comparison. Maintaining the same easy-to-follow style as the previous edition while also including modern updates, this book continues to present a new and integrated system of experimental design and analysis that can be applied across various fields of research including engineering, medicine, and the physical sciences. The authors modernize accepted methodologies while refining many cutting-edge topics including robust parameter design, reliability improvement, analysis of non-normal data, analysis of experiments with complex aliasing, multilevel designs, minimum aberration designs, and orthogonal arrays. Along with a new chapter that focuses on regression analysis, the Second Edition features expanded and new coverage of additional topics, including: Expected mean squares and sample size determination One-way and two-way ANOVA with random effects Split-plot designs ANOVA treatment of factorial effects Response surface modeling for related factors Drawing on examples from their combined years of working with industrial clients, the authors present many cutting-edge topics in a single, easily accessible source. Extensive case studies, including goals, data, and experimental designs, are also included, and the book's data sets can be found on a related FTP site, along with additional supplemental material. Chapter summaries provide a succinct outline of discussed methods, and extensive appendices direct readers to resources for further study. Experiments, Second Edition is an excellent book for design of experiments courses at the upper-undergraduate and graduate levels. It is also a valuable resource for practicing engineers and statisticians.

Statistical Software Engineering
Statistical Software Engineering

Author: National Research Council

Publisher: National Academies Press

Published: 1996-03-15

Total Pages: 83

ISBN-13: 0309176085

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This book identifies challenges and opportunities in the development and implementation of software that contain significant statistical content. While emphasizing the relevance of using rigorous statistical and probabilistic techniques in software engineering contexts, it presents opportunities for further research in the statistical sciences and their applications to software engineering. It is intended to motivate and attract new researchers from statistics and the mathematical sciences to attack relevant and pressing problems in the software engineering setting. It describes the "big picture," as this approach provides the context in which statistical methods must be developed. The book's survey nature is directed at the mathematical sciences audience, but software engineers should also find the statistical emphasis refreshing and stimulating. It is hoped that the book will have the effect of seeding the field of statistical software engineering by its indication of opportunities where statistical thinking can help to increase understanding, productivity, and quality of software and software production.

Statistics and Probability with Applications for Engineers and Scientists
Statistics and Probability with Applications for Engineers and Scientists

Author: Bhisham C Gupta

Publisher: John Wiley & Sons

Published: 2014-03-06

Total Pages: 898

ISBN-13: 1118522206

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Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab® and Microsoft® Office Excel® to analyze various data sets. The book also features: • Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices • A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method • Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology • A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP ® routines and results Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.

Robust Estimation and Testing
Robust Estimation and Testing

Author: Robert G. Staudte

Publisher: John Wiley & Sons

Published: 2011-09-15

Total Pages: 382

ISBN-13: 1118165497

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An introduction to the theory and methods of robust statistics, providing students with practical methods for carrying out robust procedures in a variety of statistical contexts and explaining the advantages of these procedures. In addition, the text develops techniques and concepts likely to be useful in the future analysis of new statistical models and procedures. Emphasizing the concepts of breakdown point and influence functon of an estimator, it demonstrates the technique of expressing an estimator as a descriptive measure from which its influence function can be derived and then used to explore the efficiency and robustness properties of the estimator. Mathematical techniques are complemented by computational algorithms and Minitab macros for finding bootstrap and influence function estimates of standard errors of the estimators, robust confidence intervals, robust regression estimates and their standard errors. Includes examples and problems.

Experimental Design in Biotechnology
Experimental Design in Biotechnology

Author: Perry D. Haaland

Publisher: CRC Press

Published: 2020-11-25

Total Pages: 284

ISBN-13: 1000103706

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This book provides the first time user of statistics with an understanding of how and why statistical experimental design and analysis can be an effective problem solving tool. It presents experimental designs which are useful for small screening and response surface experiments.