Statistics for experimenters

Author: George E. P. Box
Publisher: Wiley-Blackwell
ISBN: 0471718130
Release Date: 2005-05-31
Genre: Business & Economics

A Classic adapted to modern times Rewritten and updated, this new edition of Statistics for Experimenters adopts the same approaches as the landmark First Edition by teaching with examples, readily understood graphics, and the appropriate use of computers. Catalyzing innovation, problem solving, and discovery, the Second Edition provides experimenters with the scientific and statistical tools needed to maximize the knowledge gained from research data, illustrating how these tools may best be utilized during all stages of the investigative process. The authors’ practical approach starts with a problem that needs to be solved and then examines the appropriate statistical methods of design and analysis. Providing even greater accessibility for its users, the Second Edition is thoroughly revised and updated to reflect the changes in techniques and technologies since the publication of the classic First Edition. Among the new topics included are: Graphical Analysis of Variance Computer Analysis of Complex Designs Simplification by transformation Hands-on experimentation using Response Service Methods Further development of robust product and process design using split plot arrangements and minimization of error transmission Introduction to Process Control, Forecasting and Time Series Illustrations demonstrating how multi-response problems can be solved using the concepts of active and inert factor spaces and canonical spaces Bayesian approaches to model selection and sequential experimentation An appendix featuring Quaquaversal quotes from a variety of sources including noted statisticians and scientists to famous philosophers is provided to illustrate key concepts and enliven the learning process. All the computations in the Second Edition can be done utilizing the statistical language R. Functions for displaying ANOVA and lamba plots, Bayesian screening, and model building are all included and R packages are available online. All theses topics can also be applied utilizing easy-to-use commercial software packages. Complete with applications covering the physical, engineering, biological, and social sciences, Statistics for Experimenters is designed for individuals who must use statistical approaches to conduct an experiment, but do not necessarily have formal training in statistics. Experimenters need only a basic understanding of mathematics to master all the statistical methods presented. This text is an essential reference for all researchers and is a highly recommended course book for undergraduate and graduate students.

Statistics for experimenters

Author: George E. P. Box
Publisher: Wiley-Interscience
ISBN: UOM:39015039104321
Release Date: 1978-07-06
Genre: Mathematics

Introduces the philosophy of experimentation and the part that statistics play in experimentation. Emphasizes the need to develop a capability for ``statistical thinking'' by using examples drawn from actual case studies.

Statistical Methods for Six Sigma

Author: Anand M. Joglekar
Publisher: John Wiley & Sons
ISBN: 0471465372
Release Date: 2003-09-19
Genre: Science

A guide to achieving business successes through statistical methods Statistical methods are a key ingredient in providing data-based guidance to research and development as well as to manufacturing. Understanding the concepts and specific steps involved in each statistical method is critical for achieving consistent and on-target performance. Written by a recognized educator in the field, Statistical Methods for Six Sigma: In R&D and Manufacturing is specifically geared to engineers, scientists, technical managers, and other technical professionals in industry. Emphasizing practical learning, applications, and performance improvement, Dr. Joglekar?s text shows today?s industry professionals how to: Summarize and interpret data to make decisions Determine the amount of data to collect Compare product and process designs Build equations relating inputs and outputs Establish specifications and validate processes Reduce risk and cost-of-process control Quantify and reduce economic loss due to variability Estimate process capability and plan process improvements Identify key causes and their contributions to variability Analyze and improve measurement systems This long-awaited guide for students and professionals in research, development, quality, and manufacturing does not presume any prior knowledge of statistics. It covers a large number of useful statistical methods compactly, in a language and depth necessary to make successful applications. Statistical methods in this book include: variance components analysis, variance transmission analysis, risk-based control charts, capability and performance indices, quality planning, regression analysis, comparative experiments, descriptive statistics, sample size determination, confidence intervals, tolerance intervals, and measurement systems analysis. The book also contains a wealth of case studies and examples, and features a unique test to evaluate the reader?s understanding of the subject.

Optimal Design of Experiments

Author: Peter Goos
Publisher: John Wiley & Sons
ISBN: 9781119976165
Release Date: 2011-06-28
Genre: Science

"This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.

Testing 1 2 3

Author: Johannes Ledolter
Publisher: Stanford University Press
ISBN: 0804756120
Release Date: 2007
Genre: Business & Economics

This book gives students, practitioners, and managers a set of practical and valuable tools for designing and analyzing experiments, emphasizing applications in marketing and service operations such as website design, direct mail campaigns, and in-store tests.

Probability and Statistical Inference

Author: Robert Bartoszynski
Publisher: John Wiley & Sons
ISBN: 0470191589
Release Date: 2007-11-16
Genre: Mathematics

Now updated in a valuable new edition—this user-friendly book focuses on understanding the "why" of mathematical statistics Probability and Statistical Inference, Second Edition introduces key probability and statis-tical concepts through non-trivial, real-world examples and promotes the developmentof intuition rather than simple application. With its coverage of the recent advancements in computer-intensive methods, this update successfully provides the comp-rehensive tools needed to develop a broad understanding of the theory of statisticsand its probabilistic foundations. This outstanding new edition continues to encouragereaders to recognize and fully understand the why, not just the how, behind the concepts,theorems, and methods of statistics. Clear explanations are presented and appliedto various examples that help to impart a deeper understanding of theorems and methods—from fundamental statistical concepts to computational details. Additional features of this Second Edition include: A new chapter on random samples Coverage of computer-intensive techniques in statistical inference featuring Monte Carlo and resampling methods, such as bootstrap and permutation tests, bootstrap confidence intervals with supporting R codes, and additional examples available via the book's FTP site Treatment of survival and hazard function, methods of obtaining estimators, and Bayes estimating Real-world examples that illuminate presented concepts Exercises at the end of each section Providing a straightforward, contemporary approach to modern-day statistical applications, Probability and Statistical Inference, Second Edition is an ideal text for advanced undergraduate- and graduate-level courses in probability and statistical inference. It also serves as a valuable reference for practitioners in any discipline who wish to gain further insight into the latest statistical tools.

Designing Experiments and Analyzing Data

Author: Scott E. Maxwell
Publisher: Routledge
ISBN: 9781317284550
Release Date: 2017-09-11
Genre: Psychology

Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Delaney, and Kelley first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis that is appropriate for a wide variety of designs, which allows for the introduction of more complex topics that are generally omitted from other books. Numerous pedagogical features?further facilitate understanding:?examples of published research demonstrate the applicability of each chapter’s content; flowcharts?assist in choosing the most appropriate procedure;?end-of-chapter lists of important formulas highlight key ideas and assist readers in locating the initial presentation of equations; useful programming code and tips are provided throughout the book and in associated resources available online, and?extensive sets of exercises?help develop a deeper understanding of the subject.?Detailed solutions?for some of the exercises and?realistic data sets?are included on the website (DesigningExperiments.com). The pedagogical approach used throughout the book enables readers to gain an overview of experimental design, from conceptualization of the research question to analysis of the data. The book and its companion website with web apps, tutorials, and detailed code are ideal for students and researchers seeking the optimal way to design their studies and analyze the resulting data.

An Accidental Statistician

Author: George E. P. Box
Publisher: John Wiley & Sons
ISBN: 9781118514931
Release Date: 2013-03-12
Genre: Biography & Autobiography

Celebrating the life of an admired pioneer in statistics In this captivating and inspiring memoir, world-renowned statistician George E. P. Box offers a firsthand account of his life and statistical work. Writing in an engaging, charming style, Dr. Box reveals the unlikely events that led him to a career in statistics, beginning with his job as a chemist conducting experiments for the British army during World War II. At this turning point in his life and career, Dr. Box taught himself the statistical methods necessary to analyze his own findings when there were no statisticians available to check his work. Throughout his autobiography, Dr. Box expertly weaves a personal and professional narrative to illustrate the effects his work had on his life and vice-versa. Interwoven between his research with time series analysis, experimental design, and the quality movement, Dr. Box recounts coming to the United States, his family life, and stories of the people who mean the most to him. This fascinating account balances the influence of both personal and professional relationships to demonstrate the extraordinary life of one of the greatest and most influential statisticians of our time. An Accidental Statistician also features: • Two forewords written by Dr. Box’s former colleagues and closest confidants • Personal insights from more than a dozen statisticians on how Dr. Box has influenced and continues to touch their careers and lives • Numerous, previously unpublished photos from the author’s personal collection An Accidental Statistician is a compelling read for statisticians in education or industry, mathematicians, engineers, and anyone interested in the life story of an influential intellectual who altered the world of modern statistics.

Design and Analysis of Experiments with R

Author: John Lawson
Publisher: CRC Press
ISBN: 9781498728485
Release Date: 2014-12-17
Genre: Mathematics

Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data, shows how to perform the proper analysis of the data, and illustrates the interpretation of results. Drawing on his many years of working in the pharmaceutical, agricultural, industrial chemicals, and machinery industries, the author teaches students how to: Make an appropriate design choice based on the objectives of a research project Create a design and perform an experiment Interpret the results of computer data analysis The book emphasizes the connection among the experimental units, the way treatments are randomized to experimental units, and the proper error term for data analysis. R code is used to create and analyze all the example experiments. The code examples from the text are available for download on the author’s website, enabling students to duplicate all the designs and data analysis. Intended for a one-semester or two-quarter course on experimental design, this text covers classical ideas in experimental design as well as the latest research topics. It gives students practical guidance on using R to analyze experimental data.

Design of Experiments for Engineers and Scientists

Author: Jiju Antony
Publisher: Elsevier
ISBN: 9780080994192
Release Date: 2014-02-22
Genre: Technology & Engineering

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

Response Surface Methodology

Author: Raymond H. Myers
Publisher: John Wiley & Sons
ISBN: 9781118916032
Release Date: 2016-01-04
Genre: Mathematics

Praise for the Third Edition: “This new third edition has been substantially rewritten and updated with new topics and material, new examples and exercises, and to more fully illustrate modern applications of RSM.” - Zentralblatt Math Featuring a substantial revision, the Fourth Edition of Response Surface Methodology: Process and Product Optimization Using Designed Experiments presents updated coverage on the underlying theory and applications of response surface methodology (RSM). Providing the assumptions and conditions necessary to successfully apply RSM in modern applications, the new edition covers classical and modern response surface designs in order to present a clear connection between the designs and analyses in RSM. With multiple revised sections with new topics and expanded coverage, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition includes: Many updates on topics such as optimal designs, optimization techniques, robust parameter design, methods for design evaluation, computer-generated designs, multiple response optimization, and non-normal responses Additional coverage on topics such as experiments with computer models, definitive screening designs, and data measured with error Expanded integration of examples and experiments, which present up-to-date software applications, such as JMP®, SAS, and Design-Expert®, throughout An extensive references section to help readers stay up-to-date with leading research in the field of RSM An ideal textbook for upper-undergraduate and graduate-level courses in statistics, engineering, and chemical/physical sciences, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition is also a useful reference for applied statisticians and engineers in disciplines such as quality, process, and chemistry.

Statistical control by monitoring and feedback adjustment

Author: George E. P. Box
Publisher: Wiley-Interscience
ISBN: UOM:39015040619044
Release Date: 1997-09-22
Genre: Business & Economics

A detailed, practical, accessible guide to efficient statistical control. Efficient control is a key element in the improvement and maintenance of quality and productivity. This book shows the advantages of bringing together the more commonly used methods of statistical quality control with appropriate techniques of feedback adjustment. It uses recent research and practical experience to provide feedback methods of immediate use in the workplace. Statistical Control by Monitoring and Feedback Adjustment introduces a new coordinated approach to quality control. The authors' clear and cogent presentation uses extensive graphical explanation supplemented by numerous examples and computational tables. A helpful selection of problems and solutions further facilitates understanding. Topics covered include: * A fresh look at process monitoring * Using feedback adjustment charts * Minimizing the size of adjustments * Feedback techniques that minimize costs of adjustment and sampling * Detection of special causes with Cuscore Statistics * Efficient monitoring of operating feedback systems * The roles of models, optimization, and robustness * A brief review of time series analysis. Statistical Control by Monitoring and Feedback Adjustment is important reading for quality control engineers and statisticians as well as graduate students in quality control, industrial engineering, and applied statistics.

Management Worldwide

Author: David John Hickson
Publisher: Penguin Global
ISBN: 014100603X
Release Date: 2001
Genre: Business & Economics

Fully updated and expanded for this second edition, Management Worldwide is essential for managers, students of management and organizations who want to know how managers operate and business is conducted in different societies. David Hickson and Derek Pugh describe how things work in the countries of the seven major cultural and economic groups around the world: Anglo-Saxon, Latin, northern Europe, eastern Europe, Asian, Arab and the Developing World. There is new material on Hungary, Indonesia and South Korea, and each chapter has been revised to take account of fresh research and writing from authorities worldwide. Later chapters provide profiles of the internationally minded manager and practical guidance for expatriates returning to homebase. It concludes by looking at convergence and the factors that may be slowly overcoming local differences and forging a common international management style.

RSM Simplified

Author: Mark J. Anderson
Publisher: CRC Press
ISBN: 9781315351728
Release Date: 2016-08-05
Genre: Business & Economics

Anderson and Whitcomb pick up where they left off in DOE Simplified with RSM Simplified -- a practical tool for design of experiments that anyone with a minimum of technical training can understand and appreciate. Their approach is simple and fun for those who desire knowledge on response surface methods but are put off by the academic nature of other books on the topic. RSM Simplified keeps formulas to a minimum and makes liberal use of figures, charts, graphs, and checklists. It offers many relevant examples with amusing sidebars and do-it-yourself exercises that will lead readers to the peak potential for their product quality and process efficiency.

Modern Multivariate Statistical Techniques

Author: Alan J. Izenman
Publisher: Springer Science & Business Media
ISBN: 0387781897
Release Date: 2009-03-02
Genre: Mathematics

This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.