Author: George E. P. Box
Release Date: 2009-07-14
This set contains Statistics for Experimenters: Design, Innovation, and Discovery, Second Edition by George E.P. Box, J. Stuart Hunter, and William G. Hunter (978-0-471-71813-0) and JMP(r) Version 6 Software.
Author: SAS Institute
Publisher: SAS Institute
Release Date: 2016-09-09
The JMP 13 Design of Experiments Guide covers classic DOE designs (for example, full factorial, response surface, and mixture designs). Read about more flexible custom designs, which you generate to fit your particular experimental situation. And discover JMP’s definitive screening designs, an efficient way to identify important factor interactions using fewer runs than required by traditional designs. The book also provides guidance on determining an appropriate sample size for your study.
Publisher: SAS Institute
Release Date: 2015-03-01
JMP 12 Design of Experiments Guide covers classic DOE designs (for example, full factorial, response surface, and mixture designs). Read about more flexible custom designs, which you generate to fit your particular experimental situation. Discover JMP’s definitive screening designs, an efficient way to identify important factor interactions using fewer runs than required by traditional designs. And read about creating designs that test systems where failures occur as a result of interactions among components or subsystems. The book also provides guidance on determining an appropriate sample size for your study.
This two-volume set — winner of a 2013 Highly Commended BMA Medical Book Award for Medicine — provides an in-depth look at one of the most promising avenues for advances in the diagnosis, prevention and treatment of human disease. The inclusion of the latest information on diagnostic testing, population screening, predicting disease susceptibility, pharmacogenomics and more presents this book as an essential tool for both students and specialists across many biological and medical disciplines, including human genetics and genomics, oncology, neuroscience, cardiology, infectious disease, molecular medicine, and biomedical science, as well as health policy disciplines focusing on ethical, legal, regulatory and economic aspects of genomics and medicine. Volume One Includes: Principles, Methodology and Translational Approaches, takes readers on the journey from principles of human genomics to technology, informatic and computational platforms for genomic medicine, as well as strategies for translating genomic discoveries into advances in personalized clinical care. Volume Two Includes: Genome Discoveries and Clinical Applications presents the latest developments in disease-based genomic and personalized medicine. With chapters dedicated to cardiovascular disease, oncology, inflammatory disease, metabolic disease, neuropsychiatric disease, and infectious disease, this work provides the most comprehensive guide to the principles and practice of genomic and personalized medicine. Highly Commended 2013 BMA Medical Book Award for Medicine Contributions from leaders in the field provide unparalleled insight into current technologies and applications in clinical medicine. Full colour throughout enhances the utility of this work as the only available comprehensive reference for genomic and personalized medicine. Discusses scientific foundations and practical applications of new discoveries, as well as ethical, legal/regulatory, and social issues related to the practice of genomic medicine.
Author: Robert Mee
Publisher: Springer Science & Business Media
Release Date: 2009-06-23
This book contains the most comprehensive coverage available anywhere for two-level factorial designs. The re-analysis of 50 published examples serves as a how-to guide for analysis of the many types of full factorial and fractional factorial designs. By focusing on two-level designs, this book is accessible to a wide audience of practitioners who use planned experiments.
Handbook of Design and Analysis of Experiments provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook gives a unified treatment of a wide range of topics, covering the latest developments. This carefully edited collection of 25 chapters in seven sections synthesizes the state of the art in the theory and applications of designed experiments and their analyses. Written by leading researchers in the field, the chapters offer a balanced blend of methodology and applications. The first section presents a historical look at experimental design and the fundamental theory of parameter estimation in linear models. The second section deals with settings such as response surfaces and block designs in which the response is modeled by a linear model, the third section covers designs with multiple factors (both treatment and blocking factors), and the fourth section presents optimal designs for generalized linear models, other nonlinear models, and spatial models. The fifth section addresses issues involved in designing various computer experiments. The sixth section explores "cross-cutting" issues relevant to all experimental designs, including robustness and algorithms. The final section illustrates the application of experimental design in recently developed areas. This comprehensive handbook equips new researchers with a broad understanding of the field’s numerous techniques and applications. The book is also a valuable reference for more experienced research statisticians working in engineering and manufacturing, the basic sciences, and any discipline that depends on controlled experimental investigation.
Author: William Q. Meeker
Publisher: John Wiley & Sons
Release Date: 2017-04-10
Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition—more than double the size of the first—adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on: • Likelihood-based statistical intervals • Nonparametric bootstrap intervals • Parametric bootstrap and other simulation-based intervals • An introduction to Bayesian intervals • Bayesian intervals for the popular binomial, Poisson and normal distributions • Statistical intervals for Bayesian hierarchical models • Advanced case studies, further illustrating the use of the newly described methods New technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information. Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals. William Q. Meeker is Professor of Statistics and Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He is co-author of Statistical Methods for Reliability Data (Wiley, 1998) and of numerous publications in the engineering and statistical literature and has won many awards for his research. Gerald J. Hahn served for 46 years as applied statistician and manager of an 18-person statistics group supporting General Electric and has co-authored four books. His accomplishments have been recognized by GE’s prestigious Coolidge Fellowship and 19 professional society awards. Luis A. Escobar is Professor of Statistics at Louisiana State University. He is co-author of Statistical Methods for Reliability Data (Wiley, 1998) and several book chapters. His publications have appeared in the engineering and statistical literature and he has won several research and teaching awards.
Author: Christine M. Anderson-Cook
Publisher: ASQ Quality Press
Release Date: 2016-04-22
Genre: Business & Economics
Quality Progress, the flagship journal of ASQ, has been publishing the column “Statistics Roundtable” since 1999. With over 130 contributions from leading authors in applied statistics, the column has been highly successful and widely read. This book collects 90 of the most interesting and useful articles on some key topics. The editors have constructed this book to be a resource for statisticians and practitioners alike – with short, accessible, practical advice in important core areas of statistics from world-renowned experts. This book is intended to be an informative read, with bite-sized columns, as well as a starting point for deeper exploration of key statistical areas. The book contains nine chapters with collections of articles on the following topics: Statistical engineering Data quality and measurement Data collection Key statistical tools Quality control Reliability Multiple response and meta-analysis Applications Communication and training Chapter introductions provide a quick overview of the material contained in the columns of that chapter, as well as complementary articles for that topic that appear elsewhere in the book. Also included at the end of the each chapter introduction is a short list of key references that can provide additional details or examples for material in the topic area.
Exploring roles critical to environmental toxicology, Modeling and Simulation in Ecotoxicology with Applications in MATLAB® and Simulink® covers the steps in modeling and simulation from problem conception to validation and simulation analysis. Using the MATLAB and Simulink programming languages, the book presents examples of mathematical functions and simulations, with special emphasis on how to develop mathematical models and run computer simulations of ecotoxicological processes. Designed for students and professionals with little or no experience in modeling, the book includes: General principles of modeling and simulation and an introduction to MATLAB and Simulink Stochastic modeling where variability and uncertainty are acknowledged by making parameters random variables Toxicological processes from the level of the individual organism, with worked examples of process models in either MATLAB or Simulink Toxicological processes at the level of populations, communities, and ecosystems Parameter estimation using least squares regression methods The design of simulation experiments similar to the experimental design applied to laboratory or field experiments Methods of postsimulation analysis, including stability analysis and sensitivity analysis Different levels of model validation and how they are related to the modeling purpose The book also provides three individual case studies. The first involves a model developed to assess the relative risk of mortality following exposure to insecticides in different avian species. The second explores the role of diving behavior on the inhalation and distribution of oil spill naphthalene in bottlenose dolphins. The final case study looks at the dynamics of mercury in Daphnia that are exposed to simulated thermal plumes from a hypothetical power plant cooling system. Presented in a rigorous yet accessible style, the methodology is versatile enough to be readily applicable not only to environmental toxicology but a range of other biological fields.
The practical approached championed in this book have led to increasing the quality on many successful products through providing a better understanding of consumer needs, current product and process performance and a desired future state. In 2009, Frank Rossi and Viktor Mirtchev brought their practical statistical thinking forward and created the course “Statistics for Food Scientists . The intent of the course was to help product and process developers increase the probability of their project’s success through the incorporation of practical statistical thinking in their challenges. The course has since grown and has become the basis of this book. Presents detailed descriptions of statistical concepts and commonly used statistical tools to better analyze data and interpret results Demonstrates thorough examples and specific practical problems of what food scientists face in their work and how the tools of statistics can help them to make more informed decisions Provides information to show how statistical tools are applied to improve research results, enhance product quality, and promote overall product development
Author: Anthony Atkinson
Publisher: Oxford University Press
Release Date: 2007-05-24
Genre: Business & Economics
Experiments in the field and in the laboratory cannot avoid random error and statistical methods are essential for their efficient design and analysis. Authored by leading experts in key fields, this text provides many examples of SAS code, results, plots and tables, along with a fully supported website.
Author: William Hooper
Publisher: CRC Press
Release Date: 2017-03-16
Genre: Business & Economics
This book is for those that have struggled with the concept of statistics, have a genuine fear of data, and think the world of continuous improvement and experimentation is designed for few to understand. This book answers the question, why can’t every operator, technician, student, manager and leader understand the fundamentals of data and the science of data analysis for continuous improvement. There are many books on teaching and many books on magic and juggling, but few books connect the two. This book will change the learning process by using magic and juggling to explain probability theory and statistics to front-line operators so they can understand how to utilize the data.
As technology presses forward, scientific projects are becoming increasingly complex. The international space station, for example, includes over 100 major components, carried aloft during 88 spaces flights which were organized by over 16 nations. The need for improved system integration between the elements of an overall larger technological system has sparked further development of systems of systems (SoS) as a solution for achieving interoperability and superior coordination between heterogeneous systems. Systems of Systems Engineering: Principles and Applications provides engineers with a definitive reference on this newly emerging technology, which is being embraced by such engineering giants as Boeing, Lockheed Martin, and Raytheon. The book covers the complete range of fundamental SoS topics, including modeling, simulation, architecture, control, communication, optimization, and applications. Containing the contributions of pioneers at the forefront of SoS development, the book also offers insight into applications in national security, transportation, energy, and defense as well as healthcare, the service industry, and information technology. System of systems (SoS) is still a relatively new concept, and in time numerous problems and open-ended issues must be addressed to realize its great potential. THis book offers a first look at this rapidly developing technology so that engineers are better equipped to face such challenges.
Author: Peter Bajorski
Publisher: John Wiley & Sons
Release Date: 2011-09-26
A vivid, hands-on discussion of the statistical methods in imaging, optics, and photonics applications In the field of imaging science, there is a growing need for students and practitioners to be equipped with the necessary knowledge and tools to carry out quantitative analysis of data. Providing a self-contained approach that is not too heavily statistical in nature, Statistics for Imaging, Optics, and Photonics presents necessary analytical techniques in the context of real examples from various areas within the field, including remote sensing, color science, printing, and astronomy. Bridging the gap between imaging, optics, photonics, and statistical data analysis, the author uniquely concentrates on statistical inference, providing a wide range of relevant methods. Brief introductions to key probabilistic terms are provided at the beginning of the book in order to present the notation used, followed by discussions on multivariate techniques such as: Linear regression models, vector and matrix algebra, and random vectors and matrices Multivariate statistical inference, including inferences about both mean vectors and covariance matrices Principal components analysis Canonical correlation analysis Discrimination and classification analysis for two or more populations and spatial smoothing Cluster analysis, including similarity and dissimilarity measures and hierarchical and nonhierarchical clustering methods Intuitive and geometric understanding of concepts is emphasized, and all examples are relatively simple and include background explanations. Computational results and graphs are presented using the freely available R software, and can be replicated by using a variety of software packages. Throughout the book, problem sets and solutions contain partial numerical results, allowing readers to confirm the accuracy of their approach; and a related website features additional resources including the book's datasets and figures. Statistics for Imaging, Optics, and Photonics is an excellent book for courses on multivariate statistics for imaging science, optics, and photonics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for professionals working in imaging, optics, and photonics who carry out data analyses in their everyday work.
Biotechnology for Biofuel Production and Optimization is the compilation of current research findings that cover the entire process of biofuels production from manipulation of genes and pathways to organisms and renewable feedstocks for efficient biofuel production as well as different cultivation techniques and process scale-up considerations. This book captures recent breakthroughs in the interdisciplinary areas of systems and synthetic biology, metabolic engineering, and bioprocess engineering for renewable, cleaner sources of energy. Describes state-of-the-art engineering of metabolic pathways for the production of a variety of fuel molecules Discusses recent advances in synthetic biology and metabolic engineering for rational design, construction, evaluation of novel pathways and cell chassis Covers genome engineering technologies to address complex biofuel-tolerant phenotypes for enhanced biofuel production in engineered chassis Presents the use of novel microorganisms and expanded substrate utilization strategies for production of targeted fuel molecules Explores biohybrid methods for harvesting bioenergy Discusses bioreactor design and optimization of scale-up