Introduction to Probability, Second Edition, Joseph K. Blitzstein, Jessica Hwang
Старое издание
Автор: James Gareth Название: An Introduction to Statistical Learning ISBN: 1461471370 ISBN-13(EAN): 9781461471370 Издательство: Springer Рейтинг: Цена: 9948 р. Наличие на складе: Невозможна поставка.
Описание: This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.
Автор: Mario Lefebvre Название: Basic Probability Theory with Applications ISBN: 0387749942 ISBN-13(EAN): 9780387749945 Издательство: Springer Рейтинг: Цена: 11478 р. Наличие на складе: Невозможна поставка.
Описание: Presents elementary probability theory with applications that illustrate the theory. This book reviews the basic elements of differential calculus which are used in the material to follow. It is suitable for students in pure and applied sciences such as mathematics, engineering, computer science, finance and economics.
Описание: Updated to conform to Mathematica (R) 7.0, this second edition shows how to easily create simulations from templates and solve problems using Mathematica. Along with new sections on order statistics, transformations of multivariate normal random variables, and Brownian motion, this edition offers an expanded section on
Автор: Durrett, Rick Название: Elementary probability for applications ISBN: 0521867568 ISBN-13(EAN): 9780521867566 Издательство: Cambridge Academ Рейтинг: Цена: 11495 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is a perfect one-semester introduction to probability, for students who are familiar with basic calculus. The lively style reflects the author`s philosophy that the best way to learn probability is to see it in action, and he gives over 200 examples from genetics, sports, finance, and current events.
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.
A complete guide to the theory and practical applications of probability theory
An Introduction to Probability Theory and Its Applications uniquely blends a comprehensive overview of probability theory with the real-world application of that theory. Beginning with the background and very nature of probability theory, the book then proceeds through sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, stochastic processes, and more. The book's comprehensive approach provides a complete view of theory along with enlightening examples along the way.
Автор: Schay G. Название: Introduction to Probability with Statistical Applications ISBN: 3319306189 ISBN-13(EAN): 9783319306186 Издательство: Springer Рейтинг: Цена: 10254 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Now inits second edition, this textbook serves as an introduction toprobability and statistics for non-mathematics majors who do not need theexhaustive detail and mathematical depth provided in more comprehensivetreatments of the subject. The presentation covers the mathematical laws ofrandom phenomena, including discrete and continuous random variables,expectation and variance, and common probability distributions such as thebinomial, Poisson, and normal distributions. More classical examples such asMontmort's problem, the ballot problem, and Bertrand’s paradox are nowincluded, along with applications such as the Maxwell-Boltzmann andBose-Einstein distributions in physics.Keyfeatures in new edition:* 35 newexercises* Expanded sectionon the algebra of sets *Expanded chapters on probabilities to include more classical examples* Newsection on regression* Onlineinstructors' manual containing solutions to all exercises
Автор: Joshi Название: Introduction to Mathematical Portfolio Theory ISBN: 1107042313 ISBN-13(EAN): 9781107042315 Издательство: Cambridge Academ Рейтинг: Цена: 9436 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A concise yet comprehensive guide to the mathematics of portfolio theory from a modelling perspective, with discussion of the assumptions, limitations and implementations of the models as well as the theory underlying them. Aimed at advanced undergraduates, this book can be used for self-study or as a course text.
Описание: This text presents notions and ideas at the foundations of a statistical treatment of risks. Such knowledge facilitates the understanding of the influence of random phenomena and gives a deeper understanding of the possibilities offered by and algorithms found in certain software packages. Since Bayesian methods are frequently used in this field, a reasonable proportion of the presentation is devoted to such techniques. The text is written with a student in mind who has studied elementary undergraduate courses in engineering mathematics, maybe including a minor course in statistics. Despite employment of the style of presentation traditionally found in the mathematics literature (including descriptions like definitions, examples, etc.). Probability and Risk Analysis emphasizes an understanding of the theory and methods presented; hence, comments are given verbally and a reasoning is frequent. With respect to the contents (and its presentation), the ambition has not been to write just another new textbook on elementary probability and statistics. There are lots of such books, but instead the focus is on applications within the field of risk and safety analysis.
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