A First Course in the Design of Experiments

Author: John H. Skillings
Publisher: CRC Press
ISBN: 9780849396717
Format: PDF, ePub, Mobi
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Most texts on experimental design fall into one of two distinct categories. There are theoretical works with few applications and minimal discussion on design, and there are methods books with limited or no discussion of the underlying theory. Furthermore, most of these tend to either treat the analysis of each design separately with little attempt to unify procedures, or they will integrate the analysis for the designs into one general technique. A First Course in the Design of Experiments: A Linear Models Approach stands apart. It presents theory and methods, emphasizes both the design selection for an experiment and the analysis of data, and integrates the analysis for the various designs with the general theory for linear models. The authors begin with a general introduction then lead students through the theoretical results, the various design models, and the analytical concepts that will enable them to analyze virtually any design. Rife with examples and exercises, the text also encourages using computers to analyze data. The authors use the SAS software package throughout the book, but also demonstrate how any regression program can be used for analysis. With its balanced presentation of theory, methods, and applications and its highly readable style, A First Course in the Design of Experiments proves ideal as a text for a beginning graduate or upper-level undergraduate course in the design and analysis of experiments.

A First Course in Design and Analysis of Experiments

Author: Gary W. Oehlert
Publisher: W. H. Freeman
ISBN: 9780716735106
Format: PDF, Mobi
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Oehlert's text is suitable for either a service course for non-statistics graduate students or for statistics majors. Unlike most texts for the one-term grad/upper level course on experimental design, Oehlert's new book offers a superb balance of both analysis and design, presenting three practical themes to students: • when to use various designs • how to analyze the results • how to recognize various design options Also, unlike other older texts, the book is fully oriented toward the use of statistical software in analyzing experiments.

Experimental Design and Statistics for Psychology

Author: Fabio Sani
Publisher: John Wiley & Sons
ISBN: 1405150386
Format: PDF, ePub
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Experimental Design and Statistics for Psychology: A First Course is a concise, straighforward and accessible introduction to the design of psychology experiments and the statistical tests used to make sense of their results. Makes abundant use of charts, diagrams and figures. Assumes no prior knowledge of statistics. Invaluable to all psychology students needing a firm grasp of the basics, but tackling of some of the topic’s more complex, controversial issues will also fire the imagination of more ambitious students. Covers different aspects of experimental design, including dependent versus independent variables, levels of treatment, experimental control, random versus systematic errors, and within versus between subjects design. Provides detailed instructions on how to perform statistical tests with SPSS. Downloadable instructor resources to supplement and support your lectures can be found at www.blackwellpublishing.com/sani and include sample chapters, test questions, SPSS data sets, and figures and tables from the book.

Design of Experiments for Engineers and Scientists

Author: Jiju Antony
Publisher: Elsevier
ISBN: 0080469957
Format: PDF
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The tools and technique used in the Design of Experiments (DOE) have been proved successful in meeting the challenge of continuous improvement over the last 15 years. However, research has shown that applications of these techniques in small and medium-sized manufacturing companies are limited due to a lack of statistical knowledge required for their effective implementation. Although many books have been written in 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 by those using statistical methods and readers will find the concepts in this book both familiar and easy to understand. The book treats Planning, Communication, Engineering, Teamwork and Statistical Skills in separate chapters and then combines these skills through the use of many industrial case studies. Design of Experiments forms part of the suite of tools used in Six Sigma. Key features: * Provides essential DOE techniques for process improvement initiatives * Introduces simple graphical techniques as an alternative to advanced statistical methods – reducing time taken to design and develop prototypes, reducing time to reach the market * Case studies place DOE techniques in the context of different industry sectors * An excellent resource for the Six Sigma training program This book will be useful to 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. Dr Jiju Anthony is Senior Teaching Fellow at the International Manufacturing Unit at Warwick University. He is also a trainer and consultant in DOE and has worked as such for a number of companies including Motorola, Vickers, Procter and Gamble, Nokia, Bosch and a large number of SMEs. * Provides essential DOE techniques for process improvement initiatives * Introduces simple graphical techniques as an alternative to advanced statistical methods - reducing time taken to design and conduct tests * Case studies place DOE techniques in the context of different industry sectors

Statistical Design

Author: George Casella
Publisher: Springer Science & Business Media
ISBN: 0387759646
Format: PDF, Docs
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Although statistical design is one of the oldest branches of statistics, its importance is ever increasing, especially in the face of the data flood that often faces statisticians. It is important to recognize the appropriate design, and to understand how to effectively implement it, being aware that the default settings from a computer package can easily provide an incorrect analysis. The goal of this book is to describe the principles that drive good design, paying attention to both the theoretical background and the problems arising from real experimental situations. Designs are motivated through actual experiments, ranging from the timeless agricultural randomized complete block, to microarray experiments, which naturally lead to split plot designs and balanced incomplete blocks. George Casella is Distinguished Professor in the Department of Statistics at the University of Florida. He is active in many aspects of statistics, having contributed to theoretical statistics in the areas of decision theory and statistical confidence, to environmental statistics, and has more recently concentrated efforts in statistical genomics. He also maintains active research interests in the theory and application of Monte Carlo and other computationally intensive methods. He is listed as an ISI "Highly Cited Researcher." In other capacities, Professor Casella has served as Theory and Methods Editor of the Journal of the American Statistical Association, 1996-1999, Executive Editor of Statistical Science, 2001-2004, and Co-Editor of the Journal of the Royal Statistical Society, Series B, 2009-2012. He has served on the Board of Mathematical Sciences of the National Research Council, 1999-2003, and many committees of both the American Statistical Association and the Institute of Mathematical Statistics. Professor Casella has co-authored five textbooks: Variance Components, 1992; Theory of Point Estimation, Second Edition, 1998; Monte Carlo Statistical Methods, Second Edition, 2004; Statistical Inference, Second Edition, 2001, and Statistical Genomics of Complex Traits, 2007.

Design of Experiments

Author: Max Morris
Publisher: CRC Press
ISBN: 1439894906
Format: PDF, ePub
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Offering deep insight into the connections between design choice and the resulting statistical analysis, Design of Experiments: An Introduction Based on Linear Models explores how experiments are designed using the language of linear statistical models. The book presents an organized framework for understanding the statistical aspects of experimental design as a whole within the structure provided by general linear models, rather than as a collection of seemingly unrelated solutions to unique problems. The core material can be found in the first thirteen chapters. These chapters cover a review of linear statistical models, completely randomized designs, randomized complete blocks designs, Latin squares, analysis of data from orthogonally blocked designs, balanced incomplete block designs, random block effects, split-plot designs, and two-level factorial experiments. The remainder of the text discusses factorial group screening experiments, regression model design, and an introduction to optimal design. To emphasize the practical value of design, most chapters contain a short example of a real-world experiment. Details of the calculations performed using R, along with an overview of the R commands, are provided in an appendix. This text enables students to fully appreciate the fundamental concepts and techniques of experimental design as well as the real-world value of design. It gives them a profound understanding of how design selection affects the information obtained in an experiment.

Design of Experiments with MINITAB

Author: Paul G. Mathews
Publisher: ASQ Quality Press
ISBN: 0873896378
Format: PDF
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Most of the classic DOE books were written before DOE software was generally available, so the technical level that they assumed was that of the engineer or scientist who had to write his or her own analysis software. In this practical introduction to DOE, guided by the capabilities of the common software packages, Paul Mathews presents the basic types and methods of designed experiments appropriate for engineers, scientists, quality engineers, and Six Sigma Black Belts and Master Black Belts. Although instructions in the use of MINITAB are detailed enough to provide effective guidance to a new MINITAB user, the book is still general enough to be very helpful to users of other DOE software packages. Every chapter contains many examples with detailed solutions including extensive output from MINITAB. Preview a sample chapter from this book along with the full table of contents by clicking here.You will need Adobe Acrobat to view this pdf file.

Foundations and Methods of Stochastic Simulation

Author: Barry Nelson
Publisher: Springer Science & Business Media
ISBN: 146146160X
Format: PDF, ePub, Mobi
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This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works. It introduces object-oriented programming for simulation, covers both the probabilistic and statistical basis for simulation in a rigorous but accessible manner (providing all necessary background material); and provides a modern treatment of experiment design and analysis that goes beyond classical statistics. The book emphasizes essential foundations throughout, rather than providing a compendium of algorithms and theorems and prepares the reader to use simulation in research as well as practice. The book is a rigorous, but concise treatment, emphasizing lasting principles but also providing specific training in modeling, programming and analysis. In addition to teaching readers how to do simulation, it also prepares them to use simulation in their research; no other book does this. An online solutions manual for end of chapter exercises is also be provided.​

Designing Experiments and Analyzing Data

Author: Scott E. Maxwell
Publisher: Psychology Press
ISBN: 0805837183
Format: PDF, Mobi
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Through this book's unique model comparison approach, students and researchers are introduced to a set of fundamental principles for analyzing data. After seeing how these principles can be applied in simple designs, students are shown how these same principles also apply in more complicated designs. Drs. Maxwell and Delaney believe that the model comparison approach better prepares students to understand the logic behind a general strategy of data analysis appropriate for various designs; and builds a stronger foundation, which allows for the introduction of more complex topics omitted from other books. Several learning tools further strengthen the reader's understanding: *flowcharts assist in choosing the most appropriate technique; *an equation cross-referencing system aids in locating the initial, detailed definition and numerous summary equation tables assist readers in understanding differences between different methods for analyzing their data; *examples based on actual research in a variety of behavioral sciences help students see the applications of the material; *numerous exercises help develop a deeper understanding of the subject. Detailed solutions are provided for some of the exercises and *realistic data sets allow the reader to see an analysis of data from each design in its entirety. Updated throughout, the second edition features: *significantly increased attention to measures of effects, including confidence intervals, strength of association, and effect size estimation for complex and simple designs; *an increased use of statistical packages and the graphical presentation of data; *new chapters (15 & 16) on multilevel models; *the current controversies regarding statistical reasoning, such as the latest debates on hypothesis testing (ch. 2); *a new preview of the experimental designs covered in the book (ch. 2); *a CD with SPSS and SAS data sets for many of the text exercises, as well as tutorials reviewing basic statistics and regression; and *a Web site containing examples of SPSS and SAS syntax for analyzing many of the text exercises. Appropriate for advanced courses on experimental design or analysis, applied statistics, or analysis of variance taught in departments of psychology, education, statistics, business, and other social sciences, the book is also ideal for practicing researchers in these disciplines. A prerequisite of undergraduate statistics is assumed. An Instructor's Solutions Manual is available to those who adopt the book for classroom use.

Design of Experiments Using The Taguchi Approach

Author: Ranjit K. Roy
Publisher: John Wiley & Sons
ISBN: 9780471361015
Format: PDF, Kindle
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Accompanying CD-ROM contains ... "Qualitek-4: automatic design & analysis of Taguchi experiments (full featured working model - demo); all the examples, exercise solutions, and case studies in the book."--CD-ROM label.