Design of Experiments

Statistical Principles of Research Design and Analysis

Author: R. O. Kuehl

Publisher: Duxbury Press

ISBN: 9780534368340

Category: Mathematics

Page: 666

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Robert Kuehl's DESIGN OF EXPERIMENTS, Second Edition, prepares students to design and analyze experiments that will help them succeed in the real world. Kuehl uses a large array of real data sets from a broad spectrum of scientific and technological fields. This approach provides realistic settings for conducting actual research projects. Next, he emphasizes the importance of developing a treatment design based on a research hypothesis as an initial step, then developing an experimental or observational study design that facilitates efficient data collection. In addition to a consistent focus on research design, Kuehl offers an interpretation for each analysis.

Statistical Principles of Research Design and Analysis

Author: R. O. Kuehl

Publisher: Duxbury Resource Center

ISBN: 9780534188047

Category: Numerical analysis

Page: 686

View: 4402

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By emphasizing how research hypotheses relate to treatment design, this text provides an overall research design strategy. The author offers as realistic a setting as possible for conducting an actual research project.Examples, often based on actual research studies, describe the research venue and establish a specific problem; then the corresponding research hypothesis is identified with a treatment design that addresses it. The examples provide practical pointers relating the treatment design to the experiment design. The author includes: -- Recurrent emphasis on the following ideas: controlling variation, randomization, the "why" of replication, and the structure of the research design process-- Examples, based whenever possible on actual research studies, organized in a problem-solving fashion-- Numerous exercises also based on actual research studies and real data, whenever possible-- Consistent emphasis on data analysis of the design-- Strong computer orientation with computer outputs in SAS, SPSS, Minitab "RM", and BMDP-- A large array of real data sets from a broad spectrum of scientific and technological fields.

Design of Experiments, Statistical Principles of Research Design and Analysis

Author: CTI Reviews

Publisher: Cram101 Textbook Reviews

ISBN: 1497027160

Category: Education

Page: 30

View: 7124

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Facts101 is your complete guide to Design of Experiments, Statistical Principles of Research Design and Analysis. In this book, you will learn topics such as Treatment Comparisons, Diagnosing Agreement Between the Data and the Model, Experiments to Study Variances, and Factorial Treatment Designs plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

The Design of Experiments

Statistical Principles for Practical Applications

Author: R. Mead

Publisher: Cambridge University Press

ISBN: 9780521287623

Category: Mathematics

Page: 620

View: 1655

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In all the experimental sciences, good design of experiments is crucial to the success of research. Well-planned experiments can provide a great deal of information efficiently and can be used to test several hypotheses simultaneously. This book is about the statistical principles of good experimental design and is intended for all applied statisticians and practising scientists engaged in the design, implementation and analysis of experiments. Professor Mead has written the book with the emphasis on the logical principles of statistical design and employs a minimum of mathematics. Throughout he assumes that the large-scale analysis of data will be performed by computers and he is thus able to devote more attention to discussions of how all of the available information can be used to extract the clearest answers to many questions. The principles are illustrated with a wide range of examples drawn from medicine, agriculture, industry and other disciplines. Numerous exercises are given to help the reader practise techniques and to appreciate the difference that good design of experiments can make to a scientific project.

Statistical Analysis of Designed Experiments

Theory and Applications

Author: Ajit C. Tamhane

Publisher: John Wiley & Sons

ISBN: 1118491432

Category: Science

Page: 720

View: 6352

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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.

Design and Analysis of Experiments, Volume 1

Introduction to Experimental Design

Author: Klaus Hinkelmann,Oscar Kempthorne

Publisher: John Wiley & Sons

ISBN: 9780470191743

Category: Mathematics

Page: 640

View: 6460

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This user-friendly new edition reflects a modern and accessible approach to experimental design and analysis Design and Analysis of Experiments, Volume 1, Second Edition provides a general introduction to the philosophy, theory, and practice of designing scientific comparative experiments and also details the intricacies that are often encountered throughout the design and analysis processes. With the addition of extensive numerical examples and expanded treatment of key concepts, this book further addresses the needs of practitioners and successfully provides a solid understanding of the relationship between the quality of experimental design and the validity of conclusions. This Second Edition continues to provide the theoretical basis of the principles of experimental design in conjunction with the statistical framework within which to apply the fundamental concepts. The difference between experimental studies and observational studies is addressed, along with a discussion of the various components of experimental design: the error-control design, the treatment design, and the observation design. A series of error-control designs are presented based on fundamental design principles, such as randomization, local control (blocking), the Latin square principle, the split-unit principle, and the notion of factorial treatment structure. This book also emphasizes the practical aspects of designing and analyzing experiments and features: Increased coverage of the practical aspects of designing and analyzing experiments, complete with the steps needed to plan and construct an experiment A case study that explores the various types of interaction between both treatment and blocking factors, and numerical and graphical techniques are provided to analyze and interpret these interactions Discussion of the important distinctions between two types of blocking factors and their role in the process of drawing statistical inferences from an experiment A new chapter devoted entirely to repeated measures, highlighting its relationship to split-plot and split-block designs Numerical examples using SAS® to illustrate the analyses of data from various designs and to construct factorial designs that relate the results to the theoretical derivations Design and Analysis of Experiments, Volume 1, Second Edition is an ideal textbook for first-year graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, pharmacology, psychology, and business.

Statistical Methods in Biology

Design and Analysis of Experiments and Regression

Author: S.J. Welham,S.A. Gezan,S.J. Clark,A. Mead

Publisher: CRC Press

ISBN: 1439808783

Category: Mathematics

Page: 608

View: 742

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Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors’ experience. Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat® statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R. By the time you reach the end of the book (and online material) you will have gained: A clear appreciation of the importance of a statistical approach to the design of your experiments, A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables, Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly, An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working. The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.

Research Design and Statistical Analysis

Third Edition

Author: Jerome L. Myers,Arnold D. Well,Robert F. Lorch Jr

Publisher: Routledge

ISBN: 1135811636

Category: Psychology

Page: 832

View: 4243

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Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The book’s goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations. Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions. Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations, emphasis is also placed on data exploration, effect size measures, confidence intervals, and using power analyses to determine sample size. "Real-world" data sets are used to illustrate data exploration, analysis, and interpretation. The book offers a rare blend of the underlying statistical assumptions, the consequences of their violations, and practical advice on dealing with them. Changes in the New Edition: Each section of the book concludes with a chapter that provides an integrated example of how to apply the concepts and procedures covered in the chapters of the section. In addition, the advantages and disadvantages of alternative designs are discussed. A new chapter (1) reviews the major steps in planning and executing a study, and the implications of those decisions for subsequent analyses and interpretations. A new chapter (13) compares experimental designs to reinforce the connection between design and analysis and to help readers achieve the most efficient research study. A new chapter (27) on common errors in data analysis and interpretation. Increased emphasis on power analyses to determine sample size using the G*Power 3 program. Many new data sets and problems. More examples of the use of SPSS (PASW) Version 17, although the analyses exemplified are readily carried out by any of the major statistical software packages. A companion website with the data used in the text and the exercises in SPSS and Excel formats; SPSS syntax files for performing analyses; extra material on logistic and multiple regression; technical notes that develop some of the formulas; and a solutions manual and the text figures and tables for instructors only. Part 1 reviews research planning, data exploration, and basic concepts in statistics including sampling, hypothesis testing, measures of effect size, estimators, and confidence intervals. Part 2 presents between-subject designs. The statistical models underlying the analysis of variance for these designs are emphasized, along with the role of expected mean squares in estimating effects of variables, the interpretation of nteractions, and procedures for testing contrasts and controlling error rates. Part 3 focuses on repeated-measures designs and considers the advantages and disadvantages of different mixed designs. Part 4 presents detailed coverage of correlation and bivariate and multiple regression with emphasis on interpretation and common errors, and discusses the usefulness and limitations of these procedures as tools for prediction and for developing theory. This is one of the few books with coverage sufficient for a 2-semester course sequence in experimental design and statistics as taught in psychology, education, and other behavioral, social, and health sciences. Incorporating the analyses of both experimental and observational data provides continuity of concepts and notation. Prerequisites include courses on basic research methods and statistics. The book is also an excellent resource for practicing researchers.

The Design of Everyday Things

Psychologie und Design der alltäglichen Dinge

Author: Norman Don

Publisher: Vahlen

ISBN: 3800648105

Category: Business & Economics

Page: 320

View: 7445

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Apple, Audi, Braun oder Samsung machen es vor: Gutes Design ist heute eine kritische Voraussetzung für erfolgreiche Produkte. Dieser Klassiker beschreibt die fundamentalen Prinzipien, um Dinge des täglichen Gebrauchs umzuwandeln in unterhaltsame und zufriedenstellende Produkte. Don Norman fordert ein Zusammenspiel von Mensch und Technologie mit dem Ziel, dass Designer und Produktentwickler die Bedürfnisse, Fähigkeiten und Handlungsweisen der Nutzer in den Vordergrund stellen und Designs an diesen angepasst werden. The Design of Everyday Things ist eine informative und spannende Einführung für Designer, Marketer, Produktentwickler und für alle an gutem Design interessierten Menschen. Zum Autor Don Norman ist emeritierter Professor für Kognitionswissenschaften. Er lehrte an der University of California in San Diego und der Northwest University in Illinois. Mitte der Neunzigerjahre leitete Don Norman die Advanced Technology Group bei Apple. Dort prägte er den Begriff der User Experience, um über die reine Benutzbarkeit hinaus eine ganzheitliche Erfahrung der Anwender im Umgang mit Technik in den Vordergrund zu stellen. Norman ist Mitbegründer der Beratungsfirma Nielsen Norman Group und hat unter anderem Autohersteller von BMW bis Toyota beraten. „Keiner kommt an Don Norman vorbei, wenn es um Fragen zu einem Design geht, das sich am Menschen orientiert.“ Brand Eins 7/2013 „Design ist einer der wichtigsten Wettbewerbsvorteile. Dieses Buch macht Spaß zu lesen und ist von größter Bedeutung.” Tom Peters, Co-Autor von „Auf der Suche nach Spitzenleistungen“

Causes and Consequences of Forest Growth Trends in Europe

Results of the Recognition Project

Author: Hans-Peter Kahle

Publisher: BRILL

ISBN: 9004167056

Category: Science

Page: 261

View: 998

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Forest growth in Europe has been increasing during the last decades. Several possible causes have been suggested. In this book complementary approaches are used to discriminate between factors. Increased nitrogen availability is indicated as the major cause of the observed growth increase. In the future, direct temperature effects and increasing atmospheric carbon dioxide concentration are likely to become more important.

An Introduction To High Content Screening

Imaging Technology, Assay Development, and Data Analysis in Biology and Drug Discovery

Author: Steven A. Haney,Douglas Bowman,Arijit Chakravarty,Anthony Davies,Caroline Shamu

Publisher: John Wiley & Sons

ISBN: 0470624566

Category: Science

Page: 360

View: 8122

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Using a collaborative and interdisciplinary author base with experience in the pharmaceutical industry and academia, this book is a practical resource for high content (HC) techniques. Instructs readers on the fundamentals of high content screening (HCS) techniques Focuses on practical and widely–used techniques like image processing and multiparametric assays Breaks down HCS into individual modules for training and connects them at the end Includes a tutorial chapter that works through sample HCS assays, glossary, and detailed appendices

Design and Analysis of Experiments

Author: Angela M. Dean,Daniel Voss

Publisher: Springer Science & Business Media

ISBN: 0387985611

Category: Mathematics

Page: 742

View: 2176

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This book offers a step-by-step guide to the experimental planning process and the ensuing analysis of normally distributed data, emphasizing the practical considerations governing the design of an experiment. Data sets are taken from real experiments and sample SAS programs are included with each chapter. Experimental design is an essential part of investigation and discovery in science; this book will serve as a modern and comprehensive reference to the subject.

Statistical Principles for the Design of Experiments

Applications to Real Experiments

Author: R. Mead,S. G. Gilmour,A. Mead

Publisher: Cambridge University Press

ISBN: 0521862140

Category: Mathematics

Page: 572

View: 711

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Focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis in various disciplines.

Experimental Design in Behavioural Research

Author: Krishan D. Broota

Publisher: New Age International

ISBN: 9788122402155

Category: Social sciences

Page: 460

View: 603

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The Book Has Been Addressed To The Students And Researchers In The Disciplines Of Psychology, Education, Sociology, Social-Work, Medicine, Management, And Allied Disciplines. It Has Been Written For Those Who Do Not Possess Sophisticated Mathematical Background. Various Designs And Their Analyses Have Been Presented In Simple Understandable Language. The Intended Emphasis Is To Make The Reader Understand The Basic Principles Of Experimental Design, Layout For Data Collection, Analysis Of Data, Interpretation Of Results Of Experimental Outcome. It Offers An Integrated Approach Placing Due Emphasis On Theory, Application, And Computational Procedures. Schematic Representations Of Analysis For Each Design Is A Novel Feature Of This Book, It Makes The Analysis Simple And Easy To Comprehend. Each Design Includes General Layout For Data Collection, Schematic Representation Of The Analysis, Followed By Numerical Example With Detailed Solution And Interpretation. Numerous Illustrations, Many From Published Research, Are Provided With The Intent To Equip The Reader To Develop Insight Into The Intricacies Of Research Strategy. Special Treatment Has Been Given To Within Subject And Mixed Designs. Multivariate Analysis Of Variance, Analysis Of Covariance, And Also Analysis Of Variance By Ranks Have Been Included.

Design and Analysis of Experiments, Special Designs and Applications

Author: Klaus Hinkelmann,Oscar Kempthorne

Publisher: John Wiley & Sons

ISBN: 0470530685

Category: Mathematics

Page: 600

View: 5639

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This book discusses special modifications and extensions of designs that arise in certain fields of application such as genetics, bioinformatics, agriculture, medicine, manufacturing, marketing, etc. Well-known and highly-regarded contributors have written individual chapters that have been extensively reviewed by the Editor to ensure that each individual contribution relates to material found in Volumes 1 and 2 of this book series. The chapters in Volume 3 have an introductory/historical component and proceed to a more advanced technical level to discuss the latest results and future developm.

Design and Analysis of Experiments, Volume 3

Special Designs and Applications

Author: Klaus Hinkelmann

Publisher: John Wiley & Sons

ISBN: 1118147642

Category: Mathematics

Page: 600

View: 6105

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Provides timely applications, modifications, and extensions ofexperimental designs for a variety of disciplines Design and Analysis of Experiments, Volume 3: Special Designsand Applications continues building upon the philosophicalfoundations of experimental design by providing important, modernapplications of experimental design to the many fields that utilizethem. The book also presents optimal and efficient designs forpractice and covers key topics in current statistical research. Featuring contributions from leading researchers and academics,the book demonstrates how the presented concepts are used acrossvarious fields from genetics and medicinal and pharmaceuticalresearch to manufacturing, engineering, and national security. Eachchapter includes an introduction followed by the historicalbackground as well as in-depth procedures that aid in theconstruction and analysis of the discussed designs. Topicalcoverage includes: Genetic cross experiments, microarray experiments, and varietytrials Clinical trials, group-sequential designs, and adaptivedesigns Fractional factorial and search, choice, and optimal designs forgeneralized linear models Computer experiments with applications to homeland security Robust parameter designs and split-plot type response surfacedesigns Analysis of directional data experiments Throughout the book, illustrative and numerical examples utilizeSAS®, JMP®, and R software programs to demonstrate thediscussed techniques. Related data sets and software applicationsare available on the book's related FTP site. Design and Analysis of Experiments, Volume 3 is an idealtextbook for graduate courses in experimental design and alsoserves as a practical, hands-on reference for statisticians andresearchers across a wide array of subject areas, includingbiological sciences, engineering, medicine, and business.

The Design and Statistical Analysis of Animal Experiments

Author: Simon T. Bate,Robin A. Clark

Publisher: Cambridge University Press

ISBN: 1107782902

Category: Medical

Page: N.A

View: 3241

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Written for animal researchers, this book provides a comprehensive guide to the design and statistical analysis of animal experiments. It has long been recognised that the proper implementation of these techniques helps reduce the number of animals needed. By using real-life examples to make them more accessible, this book explains the statistical tools employed by practitioners. A wide range of design types are considered, including block, factorial, nested, cross-over, dose-escalation and repeated measures and techniques are introduced to analyse the experimental data generated. Each analysis technique is described in non-mathematical terms, helping readers without a statistical background to understand key techniques such as t-tests, ANOVA, repeated measures, analysis of covariance, multiple comparison tests, non-parametric and survival analysis. This is also the first text to describe technical aspects of InVivoStat, a powerful open-source software package developed by the authors to enable animal researchers to analyse their data and obtain informative results.

An Introduction to the Design and Analysis of Experiments in Behavioral Research

Author: John J. Kennedy,Andrew J. Bush

Publisher: University Press of America

ISBN: 9780819148070

Category: Education

Page: 576

View: 5550

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This second edition is still designed for graduate students and researchers in the social, behavioral and health sciences who have modest backgrounds in mathematics and statistics. Also, priority is still given to the discussion of seminal ideas that underlie the analysis of variance. With respect to the first edition, the late Jum C. Nunnally of Vanderbilt University remarked, 'Overall, there is no better text on statistics in the behavioral sciences available, and I strongly recommend it.' A new feature is the optional availability of a microcomputer software package, MICRO-ANOVA, that will enable researchers to perform all analyses presented in the text on IBM PCs or equivalent computers. The software package is available through UPA.

Experiment Design and Statistical Methods For Behavioural and Social Research

Author: David R. Boniface

Publisher: CRC Press

ISBN: 9780412542305

Category: Mathematics

Page: 272

View: 9396

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Experiment Design and Statistical Methods introduces the concepts, principles, and techniques for carrying out a practical research project either in real world settings or laboratories - relevant to studies in psychology, education, life sciences, social sciences, medicine, and occupational and management research. The text covers: repeated measures unbalanced and non-randomized experiments and surveys choice of design adjustment for confounding variables model building and partition of variance covariance multiple regression Experiment Design and Statistical Methods contains a unique extension of the Venn diagram for understanding non-orthogonal design, and it includes exercises for developing the reader's confidence and competence. The book also examines advanced techniques for users of computer packages or data analysis, such as Minitab, SPSS, SAS, SuperANOVA, Statistica, BMPD, SYSTAT, Genstat, and GLIM.