Statistics for business and economics, Peren, Franz W.

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10061.00 р.
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Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Автор: Senn, Stephen
Название: Dicing with death
ISBN: 1108999867 ISBN-13(EAN): 9781108999861
Издательство: Cambridge Academ
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Цена: 3325.00 р.
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Описание: From measles to malaria, from clinical trials to COVID and from life tables to the law, the second edition of Dicing with Death explains how the vital decisions we have to make both individually and collectively can be informed and improved by good data, statistical reasoning and analysis.

Автор: James, Gareth Witten, Daniela Hastie, Trevor Tibsh
Название: Introduction to statistical learning
ISBN: 1071614177 ISBN-13(EAN): 9781071614174
Издательство: Springer
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Цена: 7317.00 р.
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Описание: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more.

Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers.

An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Название: Mathematics for Machine Learning
ISBN: 110845514X ISBN-13(EAN): 9781108455145
Издательство: Cambridge Academ
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Цена: 6334.00 р.
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Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

Автор: David C. M. Dickson, Howard R. Waters, Mary R. Hardy
Название: Actuarial mathematics for life contingent risks
ISBN: 1108478085 ISBN-13(EAN): 9781108478083
Издательство: Cambridge Academ
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Цена: 13147.00 р.
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Описание: This new edition, designed as a primary text for undergraduate and graduate students, covers the mathematics of life and long-term health insurance and pensions. Exam-style questions build up students` confidence in applying the material to real-world situations, and prepares them for professional exams such as the Society of Actuaries` LTAM Exam.

Автор: Bradley Efron , Trevor Hastie
Название: Computer Age Statistical Inference, Student Edition
ISBN: 1108823416 ISBN-13(EAN): 9781108823418
Издательство: Cambridge Academ
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Цена: 5069.00 р.
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Описание: Computing power has revolutionized the theory and practice of statistical inference. Now in paperback, and fortified with 130 class-tested exercises, this book explains modern statistical thinking from classical theories to state-of-the-art prediction algorithms. Anyone who applies statistical methods to data will value this landmark text.

Автор: Brunton, Steven L. (university Of Washington) Kutz
Название: Data-driven science and engineering
ISBN: 1009098489 ISBN-13(EAN): 9781009098489
Издательство: Cambridge Academ
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Цена: 7918.00 р.
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Описание: Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB (R), new chapters on reinforcement learning and physics-informed machine learning, and supplementary videos and code.

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 1493938436 ISBN-13(EAN): 9781493938438
Издательство: Springer
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Цена: 9970.00 р.
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Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Автор: Bekes, Gabor Kezdi, Gabor
Название: Data analysis for business, economics, and policy
ISBN: 1108716202 ISBN-13(EAN): 9781108716208
Издательство: Cambridge Academ
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Цена: 7918.00 р.
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Описание: Equips future data analysts with the skills they need to answer questions in business, economics, and public policy. Covering methods of exploratory, predictive, and causal analysis, it includes case studies that use real-world data and related data exercises supported by code (Stata, R, Python) and data available online.

Автор: Field, Andy Miles, Jeremy Field, Zoe
Название: Discovering statistics using r
ISBN: 1446289133 ISBN-13(EAN): 9781446289136
Издательство: Sage Publications
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Цена: 9504.00 р.
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Описание: The R version of Andy Field`s hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R - a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences.

Автор: Spokoiny Vladimir, Dickhaus Thorsten
Название: Basics of moderm mathematical Statistics
ISBN: 366251348X ISBN-13(EAN): 9783662513484
Издательство: Springer
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Цена: 6829.00 р. 9756.00 -30%
Наличие на складе: Есть (1 шт.)
Описание: The present book provides a fully self-contained introduction to the world of modern mathematical statistics, collecting the basic knowledge, concepts and findings needed for doing further research in the modern theoretical and applied statistics.

Автор: Morrison, Faith A.
Название: Uncertainty analysis for engineers and scientists
ISBN: 1108745741 ISBN-13(EAN): 9781108745741
Издательство: Cambridge Academ
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Цена: 6970.00 р.
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Описание: Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Whether you are new to the sciences or an experienced engineer, this useful text provides a practical approach to performing error analysis.