Statistical Principles of Research Design and Analysis

Author: R. O. Kuehl

Publisher: Duxbury Resource Center

ISBN: 9780534188047

Category: Numerical analysis

Page: 686

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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: 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.

The Design of Experiments

Statistical Principles for Practical Applications

Author: R. Mead

Publisher: Cambridge University Press

ISBN: 9780521287623

Category: Mathematics

Page: 620

View: 8042

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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.

Design of Experiments, Statistical Principles of Research Design and Analysis

Author: CTI Reviews

Publisher: Cram101 Textbook Reviews

ISBN: 1497027160

Category: Education

Page: 30

View: 2753

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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 as those in your book 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.

Design and Analysis of Experiments, Introduction to Experimental Design

Author: Klaus Hinkelmann,Oscar Kempthorne

Publisher: John Wiley & Sons

ISBN: 9780470191743

Category: Mathematics

Page: 640

View: 5868

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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.

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: 8563

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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.

Studyguide for Design of Experiments

Statistical Principles of Research Design and Analysis by Kuehl, Robert O., ISBN 9780534368340

Author: Cram101 Textbook Reviews

Publisher: Cram101

ISBN: 9781497022324

Category:

Page: 120

View: 1444

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Never HIGHLIGHT a Book Again! Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9780534368340. This item is printed on demand.

The Principles of Experimental Research

Author: K. Srinagesh

Publisher: Butterworth-Heinemann

ISBN: 9780750679268

Category: Science

Page: 410

View: 532

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1 Experimental Research in Science: Its Name and Nature -- 2 The Importance of Definitions -- 3 Aspects of Quantification -- 4 The Purpose and Principles Involved in Experimenting -- Part II: Planning the Experiments -- 5 Defining the Problem for Experimental Research -- 6 Stating the Problem as a Hypothesis -- 7 Designing Experiments to Suit Problems -- 8 Dealing with Factors -- 9 Factors at More Than Two Levels -- Part III: The Craft Part of Experimental Research -- 10 Searching through Published Literature -- 11 Building the Experimental Setup -- Part IV: The Art of Reasoning in Scientific Research -- 12 Logic and Scientific Research -- 13 Inferential Logic for Experimental Research -- 14 Use of Symbolic Logic -- Part V: Probability and Statistics for Experimental Research -- 15 Introduction to Probability and Statistics -- 16 Randomization, Replication, and Sampling -- 17 Further Significance of Samples -- 18 Planning the Experiments in Statistical Terms -- 19 Statistical Inference ...

Statistical Analysis of Designed Experiments

Theory and Applications

Author: Ajit C. Tamhane

Publisher: John Wiley & Sons

ISBN: 1118491432

Category: Science

Page: 720

View: 4647

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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.

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: 9019

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



Design and Analysis of Animal Studies in Pharmaceutical Development

Author: Shein-Chung Chow,Jen-pei Liu

Publisher: CRC Press

ISBN: 9780824701307

Category: Mathematics

Page: 424

View: 2924

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"Provides well-integrated, comprehensive coverage of all the major statistical designs and methods used for animal studies in pharmaceutical research and development. Demonstrates the correct way to interpret the results of animal studies in the risk assessment of biopharmaceutical products and clarifies detailed presentations with real-world examples. "

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: 9186

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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.

Experiment Design and Statistical Methods For Behavioural and Social Research

Author: David R. Boniface

Publisher: CRC Press

ISBN: 9780412542305

Category: Mathematics

Page: 272

View: 2364

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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.

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: 9878

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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.

The Design of Experiments in Neuroscience

Author: Mary Harrington

Publisher: SAGE

ISBN: 1412974321

Category: Medical

Page: 261

View: 3010

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“You are about to start on a great adventure. You are going to transition from reading about science to becoming a scientist.” -From the Preface Using engaging, disarming prose, author Mary Harrington shows neuroscience students how to go about selecting a topic, designing an experiment, analyzing the results, and publishing a paper. This text effectively illustrates basic research methods and design principles by uniquely using relevant examples from neuroscience such as the principles of design of fMRI studies, the use of transgenic mice, and conditional gene knockouts. The author also addresses basic professional ethics, fundamental statistics and data analysis tools, the range of possible experimental designs (from simple descriptive studies to multifactorial designs), and ways to control unwanted variables and avoid common pitfalls. This text is intended as either a core or supplemental text for both undergraduates and graduate students studying research methods in Neuroscience, Neuroanatomy, Neurophysiology, Neurochemistry, or Biological Psychology.

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: 3680

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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 Dean,Daniel Voss,Danel Draguljic

Publisher: Springer

ISBN: 3319522507

Category: Mathematics

Page: 842

View: 9842

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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.

Modern Experimental Design

Author: Thomas P. Ryan

Publisher: John Wiley & Sons

ISBN: 0471210773

Category: Mathematics

Page: 593

View: 5086

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A complete and well-balanced introduction to modern experimentaldesign Using current research and discussion of the topic along withclear applications, Modern Experimental Design highlightsthe guiding role of statistical principles in experimental designconstruction. This text can serve as both an applied introductionas well as a concise review of the essential types of experimentaldesigns and their applications. Topical coverage includes designs containing one or multiplefactors, designs with at least one blocking factor, split-unitdesigns and their variations as well as supersaturated andPlackett-Burman designs. In addition, the text contains extensivetreatment of: Conditional effects analysis as a proposed general method ofanalysis Multiresponse optimization Space-filling designs, including Latin hypercube and uniformdesigns Restricted regions of operability and debarredobservations Analysis of Means (ANOM) used to analyze data from varioustypes of designs The application of available software, including Design-Expert,JMP, and MINITAB This text provides thorough coverage of the topic while alsointroducing the reader to new approaches. Using a large number ofreferences with detailed analyses of datasets, ModernExperimental Design works as a well-rounded learning tool forbeginners as well as a valuable resource for practitioners.