An Introduction to Statistics: Second Edition, Carlson K & Winquist J
Новое издание
Автор: Jennifer R. Winquist, Kieth A. Carlson Название: An Introduction to Statistics: An Active Learning Approach ISBN: 1544375093 ISBN-13(EAN): 9781544375090 Издательство: Sage Publications Цена: 21067.00 р. Наличие на складе: Поставка под заказ. Описание: This updated and reorganized Third Edition of this textbook takes a workbook-style approach that encourages an active approach to learning statistics. Carefully placed reading questions throughout each chapter allow students to apply their knowledge right away.
Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
Автор: Bland, Martin (Professor of Health Statistics, Professor of Health Statistics, University of York) Название: An Introduction to Medical Statistics 4th Edition ISBN: 0199589925 ISBN-13(EAN): 9780199589920 Издательство: Oxford Academ Рейтинг: Цена: 8395.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An Introduction to Medical Statistics, fourth edition, is a `must-have` textbook. Written in an easy-to-understand style and packed with real life examples, the text clearly explains the common statistical methods seen in published research and guidelines, as well as how to interpret and analyse statistics for clinical practice.
Автор: Michael J. Crawley Название: Statistics: An Introduction using R ISBN: 0470022981 ISBN-13(EAN): 9780470022986 Издательство: Wiley Рейтинг: Цена: 4744.00 р. Наличие на складе: Поставка под заказ.
Описание: Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. *Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. *Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. *The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. *Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. *Includes numerous worked examples and exercises within each chapter. Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.
Автор: Richard A. Johnson, Gouri K. Bhattacharyya Название: Statistics: Principles and Methods, 7th Edition ISBN: 0470904119 ISBN-13(EAN): 9780470904114 Издательство: Wiley Рейтинг: Цена: 35369.00 р. Наличие на складе: Поставка под заказ.
Описание: Statistics: Principles and Methods, 7th Edition provides a comprehensive, accurate introduction to statistics for business professionals who need to learn how to apply key concepts. The chapters include real-world data, designed to make the material more relevant. The numerous examples clearly demonstrate the important points of the methods.
A Hands-On Approach to Teaching Introductory Statistics
Expanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the mathematics underlying classical statistical analysis, the modeling aspects of statistical analysis and the biological interpretation of results, and the application of statistical software in analyzing real-world problems and datasets.
New to the Second Edition
A new chapter on non-linear regression models
A new chapter that contains examples of complete data analyses, illustrating how a full-fledged statistical analysis is undertaken
Additional exercises in most chapters
A summary of statistical formulas related to the specific designs used to teach the statistical concepts
This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.
Автор: David Lucy Название: Introduction to Statistics for Forensic Scientists ISBN: 0470022019 ISBN-13(EAN): 9780470022016 Издательство: Wiley Рейтинг: Цена: 6803.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction to Statistics for Forensic Scientists is an essential introduction to the subject, gently guiding the reader through the key statistical techniques used to evaluate various types of forensic evidence.
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