Author: John A. Cornell Publisher: John Wiley & Sons ISBN: 0470907428 Category : Mathematics Languages : en Pages : 376
Book Description
The concise yet authoritative presentation of key techniques for basic mixtures experiments Inspired by the author's bestselling advanced book on the topic, A Primer on Experiments with Mixtures provides an introductory presentation of the key principles behind experimenting with mixtures. Outlining useful techniques through an applied approach with examples from real research situations, the book supplies a comprehensive discussion of how to design and set up basic mixture experiments, then analyze the data and draw inferences from results. Drawing from his extensive experience teaching the topic at various levels, the author presents the mixture experiments in an easy-to-follow manner that is void of unnecessary formulas and theory. Succinct presentations explore key methods and techniques for carrying out basic mixture experiments, including: Designs and models for exploring the entire simplex factor space, with coverage of simplex-lattice and simplex-centroid designs, canonical polynomials, the plotting of individual residuals, and axial designs Multiple constraints on the component proportions in the form of lower and/or upper bounds, introducing L-Pseudocomponents, multicomponent constraints, and multiple lattice designs for major and minor component classifications Techniques for analyzing mixture data such as model reduction and screening components, as well as additional topics such as measuring the leverage of certain design points Models containing ratios of the components, Cox's mixture polynomials, and the fitting of a slack variable model A review of least squares and the analysis of variance for fitting data Each chapter concludes with a summary and appendices with details on the technical aspects of the material. Throughout the book, exercise sets with selected answers allow readers to test their comprehension of the material, and References and Recommended Reading sections outline further resources for study of the presented topics. A Primer on Experiments with Mixtures is an excellent book for one-semester courses on mixture designs and can also serve as a supplement for design of experiments courses at the upper-undergraduate and graduate levels. It is also a suitable reference for practitioners and researchers who have an interest in experiments with mixtures and would like to learn more about the related mixture designs and models.
Author: John A. Cornell Publisher: John Wiley & Sons ISBN: Category : Experimental design Languages : en Pages : 344
Book Description
The general mixture problem. General remarks about response surface methods. An historical perspective. References and recommended reading. The original mixture problem. The use of independent variables. Multiple constraints on the component proportions. The analysis of mixture data. Other mixture model forms. Matrix algebra, least squares, and the analysis of variance.
Author: John A. Cornell Publisher: ASQ Quality Press ISBN: Category : Business & Economics Languages : en Pages : 108
Book Description
This set of helpful analytical tools is written for practitioners who perform and analyze mixture experiments. It is a concise treatment of techniques for designing, modeling, and interpreting data from these experiments.Contents:An Overview The Simplex-Lattice Designs and Associated Polynomial Models Multiple Constraints of the Component Proportions The Analysis of Mixture Data The Inclusion of Process Variables in Mixture Experiments
Author: Kai-Tai Fang Publisher: Springer ISBN: 9811320411 Category : Mathematics Languages : en Pages : 300
Book Description
The book provides necessary knowledge for readers interested in developing the theory of uniform experimental design. It discusses measures of uniformity, various construction methods of uniform designs, modeling techniques, design and modeling for experiments with mixtures, and the usefulness of the uniformity in block, factorial and supersaturated designs. Experimental design is an important branch of statistics with a long history, and is extremely useful in multi-factor experiments. Involving rich methodologies and various designs, it has played a key role in industry, technology, sciences and various other fields. A design that chooses experimental points uniformly scattered on the domain is known as uniform experimental design, and uniform experimental design can be regarded as a fractional factorial design with model uncertainty, a space-filling design for computer experiments, a robust design against the model specification, and a supersaturated design and can be applied to experiments with mixtures.
Author: Mark J. Anderson Publisher: Taylor & Francis ISBN: 1351677527 Category : Business & Economics Languages : en Pages : 190
Book Description
Many chemists – especially those most brilliant in their field – fail to appreciate the power of planned experimentation. They dislike the mathematical aspects of statistical analysis. In addition, these otherwise very capable chemists also dismissed predictive models based only on empirical data. Ironically, in the hands of subject matter experts like these elite chemists, the statistical methods of mixture design and analysis provide the means for rapidly converging on optimal compositions. What differentiates Formulation Simplified from the standard statistical texts on mixture design is that the authors make the topic relatively easy and fun to read. They provide a whole new collection of insighful original studies that illustrate the essentials of mixture design and analysis. Solid industrial examples are offered as problems at the end of many chapters for those who are serious about trying new tools on their own. Statistical software to do the computations can be freely accessed via a web site developed in support of this book.
Author: Klaus Hinkelmann Publisher: John Wiley & Sons ISBN: 0470530685 Category : Mathematics Languages : en Pages : 598
Book Description
Provides timely applications, modifications, and extensions of experimental designs for a variety of disciplines Design and Analysis of Experiments, Volume 3: Special Designs and Applications continues building upon the philosophical foundations of experimental design by providing important, modern applications of experimental design to the many fields that utilize them. The book also presents optimal and efficient designs for practice and covers key topics in current statistical research. Featuring contributions from leading researchers and academics, the book demonstrates how the presented concepts are used across various fields from genetics and medicinal and pharmaceutical research to manufacturing, engineering, and national security. Each chapter includes an introduction followed by the historical background as well as in-depth procedures that aid in the construction and analysis of the discussed designs. Topical coverage includes: Genetic cross experiments, microarray experiments, and variety trials Clinical trials, group-sequential designs, and adaptive designs Fractional factorial and search, choice, and optimal designs for generalized linear models Computer experiments with applications to homeland security Robust parameter designs and split-plot type response surface designs Analysis of directional data experiments Throughout the book, illustrative and numerical examples utilize SAS®, JMP®, and R software programs to demonstrate the discussed techniques. Related data sets and software applications are available on the book's related FTP site. Design and Analysis of Experiments, Volume 3 is an ideal textbook for 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, and business.
Author: Angela Dean Publisher: CRC Press ISBN: 146650434X Category : Mathematics Languages : en Pages : 946
Book Description
This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.
Author: Bradley Huitema Publisher: John Wiley & Sons ISBN: 1118067460 Category : Mathematics Languages : en Pages : 562
Book Description
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.
Author: Ronald Snee Publisher: SAS Institute ISBN: 1629605301 Category : Computers Languages : en Pages : 294
Book Description
Strategies for Formulations Development: A Step-by-Step Guide Using JMP is based on the authors' significant practical experience partnering with scientists to develop strategies to accelerate the formulation (mixtures) development process. The authors not only explain the most important methods used to design and analyze formulation experiments, but they also present overall strategies to enhance both the efficiency and effectiveness of the development process. With this book you will be able to: Approach the development process from a strategic viewpoint with the overall end result in mind. Design screening experiments to identify components that are most important to the performance of the formulation. Design optimization experiments to identify the maximum response in the design space. Analyze both screening and optimization experiments using graphical and numerical methods. Optimize multiple criteria, such as the quality, cost, and performance of product formulations. Design and analyze formulation studies that involve both formulation components and process variables using methods that reduce the required experimentation by up to 50%. Linking dynamic graphics with powerful statistics, JMP helps construct a visually compelling narrative to interactively share findings that are coherent and actionable by colleagues and decision makers. Using this book, you can take advantage of computer generated experiment designs when classical designs do not suffice, given the physical and economic constraints of the experiential environment. Strategies for Formulations Development: A Step-by-Step Guide Using JMP(R) is unique because it provides formulation scientists with the essential information they need in order to successfully conduct formulation studies in the chemical, biotech, and pharmaceutical industries.
Author: Myles Hollander Publisher: John Wiley & Sons ISBN: 1118553292 Category : Mathematics Languages : en Pages : 978
Book Description
Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.
Author: John A. Cornell
Author: John A. Cornell
Author: John A. Cornell
Author: Kai-Tai Fang
Author: Mark J. Anderson
Author: Klaus Hinkelmann
Author: Angela Dean
Author: Bradley Huitema
Author: Ronald Snee
Author: Myles Hollander