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Richard kay statistical thinking for non statisticians in drug regulation
Фото - Richard Kay Statistical Thinking for Non-Statisticians in Drug Regulation richard kay statistical thinking for non statisticians in drug regulation

Richard Kay Statisti...

Statistical Thinking for Non-Statisticians in Drug Regulation, Second...

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Фото - Daniele Martini De Success Probability Estimation with Applications to Clinical Trials richard kay statistical thinking for non statisticians in drug regulation

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Provides an introduction to the various statistical techniques involve...

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Фото - Gaston Ares Mathematical and Statistical Methods in Food Science and Technology richard kay statistical thinking for non statisticians in drug regulation

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Фото - Roger Hoerl Statistical Thinking. Improving Business Performance richard kay statistical thinking for non statisticians in drug regulation

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How statistical thinking and methodology can help you make crucial bus...

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Фото - Binghe Wang Evaluation of Drug Candidates for Preclinical Development. Pharmacokinetics, Metabolism, Pharmaceutics, and Toxicology richard kay statistical thinking for non statisticians in drug regulation

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Фото - Nikolaos Limnios Statistical Models and Methods for Reliability and Survival Analysis richard kay statistical thinking for non statisticians in drug regulation

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Statistical Models and Methods for Reliability and Survival Analysis b...

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Фото - Rand Wilcox R. Understanding and Applying Basic Statistical Methods Using R richard kay statistical thinking for non statisticians in drug regulation

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Features a straightforward and concise resource for introductory stati...

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Фото - Reinhard Viertl Statistical Methods for Fuzzy Data richard kay statistical thinking for non statisticians in drug regulation

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Statistical data are not always precise numbers, or vectors, or catego...

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Фото - Philip Dawid Causality. Statistical Perspectives and Applications richard kay statistical thinking for non statisticians in drug regulation

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A state of the art volume on statistical causality Causality: Statisti...

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Фото - Guofeng You Drug Transporters. Molecular Characterization and Role in Drug Disposition richard kay statistical thinking for non statisticians in drug regulation

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Фото - Hahn Gerald J. A Career in Statistics. Beyond the Numbers richard kay statistical thinking for non statisticians in drug regulation

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A valuable guide to a successful career as a statistician A Career in...

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Фото - Zhou Honghui Drug-Drug Interactions for Therapeutic Biologics richard kay statistical thinking for non statisticians in drug regulation

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Фото - Klara Valko Physicochemical and Biomimetic Properties in Drug Discovery, Enhanced Edition. Chromatographic Techniques for Lead Optimization richard kay statistical thinking for non statisticians in drug regulation

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Demonstrating how and why to measure physicochemical and biomimetic pr...

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Фото - Shelemyahu Zacks Examples and Problems in Mathematical Statistics richard kay statistical thinking for non statisticians in drug regulation

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Фото - Michael Stumpf Handbook of Statistical Systems Biology richard kay statistical thinking for non statisticians in drug regulation

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Фото - Paolo Colombo Inhalation Drug Delivery. Techniques and Products richard kay statistical thinking for non statisticians in drug regulation

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There has been a rapid evolution in the field of inhalation drug thera...

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Дополнительная информация:

Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R Understanding and Applying Basic Statistical Methods Using R uniquely bridges the gap between advances in the statistical literature and methods routinely used by non-statisticians. Providing a conceptual basis for understanding the relative merits and applications of these methods, the book features modern insights and advances relevant to basic techniques in terms of dealing with non-normality, outliers, heteroscedasticity (unequal variances), and curvature. Featuring a guide to R, the book uses R programming to explore introductory statistical concepts and standard methods for dealing with known problems associated with classic techniques. Thoroughly class-room tested, the book includes sections that focus on either R programming or computational details to help the reader become acquainted with basic concepts and principles essential in terms of understanding and applying the many methods currently available. Covering relevant material from a wide range of disciplines, Understanding and Applying Basic Statistical Methods Using R also includes: Numerous illustrations and exercises that use data to demonstrate the practical importance of multiple perspectives Discussions on common mistakes such as eliminating outliers and applying standard methods based on means using the remaining data Detailed coverage on R programming with descriptions on how to apply both classic and more modern methods using R A companion website with the data and solutions to all of the exercises Understanding and Applying Basic Statistical Methods Using R is an ideal textbook for an undergraduate and graduate-level statistics courses in the science and/or social science departments. The book can also serve as a reference for professional statisticians and other practitioners looking to better understand modern statistical methods as well as R programming. Rand R. Wilcox, PhD, is Professor in the Department of Psychology at the University of Southern California, Fellow of the Association for Psychological Science, and an associate editor for four statistics journals. He is also a member of the International Statistical Institute. The author of more than 320 articles published in a variety of statistical journals, he is also the author eleven other books on statistics. Dr. Wilcox is creator of WRS (Wilcox’ Robust Statistics), which is an R package for performing robust statistical methods. His main research interest includes statistical methods, particularly robust methods for comparing groups and studying associations.