experiments planning analysis and optimization statistics statistics

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Author : C. F. Jeff Wu
ISBN : 9781118211533
Genre : Mathematics
File Size : 31. 60 MB
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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.

Experiments Planning Analysis And Optimization

Author : CTI Reviews
ISBN : 9781467209151
Genre : Education
File Size : 40. 78 MB
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Facts101 is your complete guide to Experiments, Planning, Analysis, and Optimization. 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.

Fundamentals Of Statistical Experimental Design And Analysis

Author : Robert G. Easterling
ISBN : 9781118954652
Genre : Mathematics
File Size : 86. 61 MB
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Professionals in all areas – business; government; thephysical, life, and social sciences; engineering; medicine, etc.– benefit from using statistical experimental design tobetter understand their worlds and then use that understanding toimprove the products, processes, and programs they are responsiblefor. This book aims to provide the practitioners of tomorrow with amemorable, easy to read, engaging guide to statistics andexperimental design. This book uses examples, drawn from a variety of established texts,and embeds them in a business or scientific context, seasoned witha dash of humor, to emphasize the issues and ideas that led to theexperiment and the what-do-we-do-next? steps after theexperiment. Graphical data displays are emphasized as means ofdiscovery and communication and formulas are minimized, with afocus on interpreting the results that software produce. The roleof subject-matter knowledge, and passion, is also illustrated. Theexamples do not require specialized knowledge, and the lessons theycontain are transferrable to other contexts. Fundamentals of Statistical Experimental Design and Analysisintroduces the basic elements of an experimental design, and thebasic concepts underlying statistical analyses. Subsequent chaptersaddress the following families of experimental designs: Completely Randomized designs, with single or multipletreatment factors, quantitative or qualitative Randomized Block designs Latin Square designs Split-Unit designs Repeated Measures designs Robust designs Optimal designs Written in an accessible, student-friendly style, this book issuitable for a general audience and particularly for thoseprofessionals seeking to improve and apply their understanding ofexperimental design.

Statistical Analysis Of Designed Experiments

Author : Ajit C. Tamhane
ISBN : 9781118491430
Genre : Science
File Size : 34. 87 MB
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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.

Experimental Design

Author : Roger E. Kirk
ISBN : 9781483305516
Genre : Social Science
File Size : 48. 86 MB
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Experimental Design: Procedures for Behavioral Sciences, Fourth Edition is a classic text with a reputuation for accessibility and readability. It has been revised and updated to make learning design concepts even easier. Roger E. Kirk shows how three simple experimental designs can be combined to form a variety of complex designs. He provides diagrams illustrating how subjects are assigned to treatments and treatment combinations. New terms are emphasized in boldface type, there are summaries of the advantages and disadvantages of each design, and real-life examples show how the designs are used.

Springer Handbook Of Engineering Statistics

Author : Hoang Pham
ISBN : 9781852338060
Genre : Business & Economics
File Size : 71. 22 MB
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In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.

Univariate Discrete Distributions

Author : Norman L. Johnson
ISBN : 9780471715801
Genre : Mathematics
File Size : 61. 74 MB
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This Set Contains: Continuous Multivariate Distributions, Volume 1, Models andApplications, 2nd Edition by Samuel Kotz, N. Balakrishnan andNormal L. Johnson Continuous Univariate Distributions, Volume 1, 2nd Editionby Samuel Kotz, N. Balakrishnan and Normal L. Johnson Continuous Univariate Distributions, Volume 2, 2nd Editionby Samuel Kotz, N. Balakrishnan and Normal L. Johnson Discrete Multivariate Distributions by Samuel Kotz, N.Balakrishnan and Normal L. Johnson Univariate Discrete Distributions, 3rd Edition by SamuelKotz, N. Balakrishnan and Normal L. Johnson Discover the latest advances in discrete distributionstheory The Third Edition of the critically acclaimedUnivariate Discrete Distributions provides a self-contained,systematic treatment of the theory, derivation, and application ofprobability distributions for count data. Generalized zeta-functionand q-series distributions have been added and are covered indetail. New families of distributions, including Lagrangian-typedistributions, are integrated into this thoroughly revised andupdated text. Additional applications of univariate discretedistributions are explored to demonstrate the flexibility of thispowerful method. A thorough survey of recent statistical literature drawsattention to many new distributions and results for the classicaldistributions. Approximately 450 new references along with severalnew sections are introduced to reflect the current literature andknowledge of discrete distributions. Beginning with mathematical, probability, and statisticalfundamentals, the authors provide clear coverage of the key topicsin the field, including: Families of discrete distributions Binomial distribution Poisson distribution Negative binomial distribution Hypergeometric distributions Logarithmic and Lagrangian distributions Mixture distributions Stopped-sum distributions Matching, occupancy, runs, and q-series distributions Parametric regression models and miscellanea Emphasis continues to be placed on the increasing relevance ofBayesian inference to discrete distribution, especially with regardto the binomial and Poisson distributions. New derivations ofdiscrete distributions via stochastic processes and random walksare introduced without unnecessarily complex discussions ofstochastic processes. Throughout the Third Edition, extensiveinformation has been added to reflect the new role ofcomputer-based applications. With its thorough coverage and balanced presentation of theoryand application, this is an excellent and essential reference forstatisticians and mathematicians.

Multivariate Density Estimation

Author : David W. Scott
ISBN : 9781118575536
Genre : Mathematics
File Size : 33. 72 MB
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Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up-to-date coverage of the unique challenges presented in the field of data analysis. The new edition focuses on the various density estimation techniques and methods that can be used in the field of big data. Defining optimal nonparametric estimators, the Second Edition demonstrates the density estimation tools to use when dealing with various multivariate structures in univariate, bivariate, trivariate, and quadrivariate data analysis. Continuing to illustrate the major concepts in the context of the classical histogram, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition also features: Over 150 updated figures to clarify theoretical results and to show analyses of real data sets An updated presentation of graphic visualization using computer software such as R A clear discussion of selections of important research during the past decade, including mixture estimation, robust parametric modeling algorithms, and clustering More than 130 problems to help readers reinforce the main concepts and ideas presented Boxed theorems and results allowing easy identification of crucial ideas Figures in color in the digital versions of the book A website with related data sets Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition is an ideal reference for theoretical and applied statisticians, practicing engineers, as well as readers interested in the theoretical aspects of nonparametric estimation and the application of these methods to multivariate data. The Second Edition is also useful as a textbook for introductory courses in kernel statistics, smoothing, advanced computational statistics, and general forms of statistical distributions.

The Analysis Of Covariance And Alternatives

Author : Bradley Huitema
ISBN : 1118067460
Genre : Mathematics
File Size : 81. 71 MB
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A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.

Quantitative Molecular Pharmacology And Informatics In Drug Discovery

Author : Michael Lutz
ISBN : 0471988618
Genre : Medical
File Size : 36. 89 MB
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Quantitative Molecular Pharmacology and Informatics in Drug Discovery Michael Lutz, Section Head, Cheminformatics Group and Terry Kenakin, Principal Research Scientist, Glaxo Wellcome Research and Development, Research Triangle Park, NC, USA Quantitative Molecular Pharmacology and Informatics in Drug Discovery combines pharmacology, genetics and statistics to provide a complete guide to the modern drug discovery process. The book discusses the pharmacology of drug testing and provides a detailed description of the statistical methods used to analyze the resulting data. Application of genetic and genomic tools for identification of biological targets is reviewed in the context of drug discovery projects. Covering both the theoretical principles upon which the techniques are based and the practicalities of drug discovery, this informative guide. ∗ outlines in step–by–step detail the advantages and disadvantages of each technology and approach and links these to the type of chemical target being sought after in the drug discovery process; and, ∗ provides excellent demonstrations of how to use powerful pharmacological and statistical tools to optimize high–throughput screening assays. Written by two internationally known and well–regarded experts, this book is an essential reference for research and development scientists working in the pharmaceutical and biotechnology industries. It will also be useful for postgraduates studying pharmacology and applied statistics.

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