Introduction to Probability and Statistics for Engineers, Milan Holick?
Автор: T. W. Anderson Название: An Introduction to Multivariate Statistical Analysis, Third Edition ISBN: 0471360910 ISBN-13(EAN): 9780471360919 Издательство: Wiley Рейтинг: Цена: 184750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: Dekking, F.M., Kraaikamp, C., Lopuhaa Название: A Modern Introduction to Probability and Statistics: Understanding Why and How ISBN: 1849969523 ISBN-13(EAN): 9781849969529 Издательство: Springer Рейтинг: Цена: 32560.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included - this is a modern method missing in many other books
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: Chapra, Steven C. Название: Numerical methods for engineers ISBN: 007126759X ISBN-13(EAN): 9780071267595 Издательство: McGraw-Hill Рейтинг: Цена: 61770.00 T Наличие на складе: Невозможна поставка. Описание: Numerical Methods for Engineers
Автор: Vijay K. Rohatgi,A.K. Md. Ehsanes Saleh Название: An Introduction to Probability and Statistics ISBN: 111879964X ISBN-13(EAN): 9781118799642 Издательство: Wiley Рейтинг: Цена: 118220.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics.
Название: Probability And Risk Analysis: An Introduction for Engineers ISBN: 3642063462 ISBN-13(EAN): 9783642063466 Издательство: Springer Рейтинг: Цена: 83810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A textbook presenting notions and ideas at the foundations of a statistical treatment of risks. The text is unlike that found in traditional mathematics literature and differs from typical textbooks in its verbal approach to many explanations and examples.
Автор: Efron Название: An Introduction to the Bootstrap ISBN: 0412042312 ISBN-13(EAN): 9780412042317 Издательство: Taylor&Francis Рейтинг: Цена: 153120.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An exploration of the many different bootstrap techniques. It discusses useful statistical techniques through real data examples and covers nonparametric regression, density estimation, classification trees, and least median squares regression. There are numerous exercises.
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