Trade-offs are clearly identified, and the pros and cons of different alternatives are listed. This lays a solid foundation for the more application-oriented chapters. The author typically encourages the reader to understand how to appropriately apply resampling methods. However, for most of the book, the chosen approach works well and is quite engaging. Therefore, I would certainly recommend this book to anyone new to resampling techniques, or to those who are teaching introductory courses on the topic.
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Introduction to Data Science and Machine Learning
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Artificial Intelligence A Modern Approach, 1st Edition
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Manual Practitioners Guide to Resampling for Data Analysis, Data Mining, and Modeling
Its intuitive and informal style makes it suitable as a text for both students and researchers. It can serve as the basis a one- or two-semester graduate course as well as a standard handbook of statistical procedures for the practitioners' desk. Parametric, permutation, and bootstrap procedures for testing hypotheses are developed side by side. The emphasis on distribution-free permutation procedures will enable workers in applied fields to use the most powerful statistic for their applications and satisfy regulatory agency demands for methods that yield exact significance levels, not approximations.
Algebra and an understanding of discrete probability will take the reader through all but the appendix, which utilizes probability measures in its proofs. The revised and expanded text of the 3rd edition includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises. Real-world problems of missing and censored data, multiple comparisons, nonresponders, after-the-fact covariates, and outliers are dealt with at length.
New sections are added on sequential analysis and multivariate analysis plus a chapter on the exact analysis of multi-factor designs based on the recently developed theory of synchronous permutations.
The book's main features include: Detailed consideration of one-, two-, and k-sample tests, contingency tables, clinical trials, cluster analysis, multiple comparisons, multivariate analysis, and repeated measures Numerous practical applications in archeology, biology, business, climatology, clinical trials, economics, education, engineering, geology, law, medicine, and the social sciences Valuable techniques for reducing computation time Practical advice on experimental design Sections on sequential analysis Comparisons among competing bootstrap, parametric, and permutation techniques.
From a review of the first edition: "Permutation Tests is a welcome addition to the literature on this subject and will prove a valuable guide for practitioners This book has already become an important addition to my reference library. Those interested in permutation tests and its applications will enjoy reading it. The text covers a broad range of topics, and has myriad pointers to topics not directly addressed. The writing is fun to read. Permutation tests : a practical guide to resampling methods for testing hypotheses by Phillip I Good Book 38 editions published between and in English and Undetermined and held by WorldCat member libraries worldwide "This book provides a step-by-step manual on the application of permutation tests in biology, business, medicine, science, and engineering.
Its intuitive and informal style ideally makes it suitable as a text for students and researchers, whether experienced or coming to these resampling methods for the very first time. The real-world problems of missing and censored data, multiple comparisons, nonresponders, after-the-fact covariates, and outliers are dealt with at length.
A manager's guide to the design and conduct of clinical trials by Phillip I Good 22 editions published between and in English and Undetermined and held by WorldCat member libraries worldwide Provides a comprehensive primer for prospective managers. It covers every critical issue of the design and conduct of clinical trials, including study design, organization, regulatory agency liaison, data collection and analysis, as well as recruitment, software, monitoring, and reporting.
Features new examples and the latest developments in regulatory guidelines, such as e-submission procedures and computerized direct data acquisition.
It also reflects the increasing globalization of clinical trial activities, and includes new information about international standards and procedures, including the Common Technical Document and CDISC standards. Introduction to statistics through resampling methods and Microsoft Office Excel by Phillip I Good 12 editions published in in English and held by WorldCat member libraries worldwide "With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote.
Readers quickly master and learn to apply statistical methods, such as bootstrap, decision trees, t-test, and permutations to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research.
Applying statistics in the courtroom : a new approach for attorneys and expert witnesses by Phillip I Good Book 17 editions published between and in English and held by WorldCat member libraries worldwide Samples and populations - Representative samples and jury selection - Sample and survey methodology - Presenting your case - Probability concepts - Criminal law - Civil law - Environmental hazards - How large is large?