Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: James, Gareth Witten, Daniela Hastie, Trevor Tibsh Название: Introduction to statistical learning ISBN: 1071614177 ISBN-13(EAN): 9781071614174 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: McElreath, Richard Название: Statistical Rethinking ISBN: 036713991X ISBN-13(EAN): 9780367139919 Издательство: Taylor&Francis Рейтинг: Цена: 83690.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Statistical Rethinking: A Bayesian Course with Examples in R and Stan, Second Edition builds knowledge/confidence in statistical modeling. Pushes readers to perform step-by-step calculations (usually automated.) Unique, computational approach.
Автор: Edge M. D. Название: Statistical Thinking from Scratch: A Primer for Scientists ISBN: 0198827628 ISBN-13(EAN): 9780198827627 Издательство: Oxford Academ Рейтинг: Цена: 232970.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Focuses on detailed instruction in a single statistical technique, simple linear regression (SLR), with the goal of gaining tools, understanding, and intuition that can be applied to other contexts.
Автор: Albert, Jim Название: Statistical Thinking in Sports ISBN: 1584888687 ISBN-13(EAN): 9781584888680 Издательство: Taylor&Francis Рейтинг: Цена: 73490.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Hald Anders Название: A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935 ISBN: 0387464085 ISBN-13(EAN): 9780387464084 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is a history of parametric statistical inference, written by one of the most important historians of statistics of the 20th century, Anders Hald. This book can be viewed as a follow-up to his two most recent books, although this current text is much more streamlined and contains new analysis of many ideas and developments. And unlike his other books, which were encyclopedic by nature, this book can be used for a course on the topic, the only prerequisites being a basic course in probability and statistics.The book is divided into five main sections:* Binomial statistical inference;* Statistical inference by inverse probability;* The central limit theorem and linear minimum variance estimation by Laplace and Gauss;* Error theory, skew distributions, correlation, sampling distributions;* The Fisherian Revolution, 1912-1935.Throughout each of the chapters, the author provides lively biographical sketches of many of the main characters, including Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. He also examines the roles played by DeMoivre, James Bernoulli, and Lagrange, and he provides an accessible exposition of the work of R.A. Fisher.This book will be of interest to statisticians, mathematicians, undergraduate and graduate students, and historians of science.
Автор: Leavy Название: Statistics in Early Childhood and Primary Education ISBN: 9811310432 ISBN-13(EAN): 9789811310430 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This compilation focuses on the theory and conceptualisation of statistics and probability in the early years and the development of young children’s (ages 3-10) understanding of data and chance. It provides a comprehensive overview of cutting-edge international research on the development of young learners’ reasoning about data and chance in formal, informal, and non-formal educational contexts. The authors share insights into young children’s statistical and probabilistic reasoning and provide early childhood educators and researchers with a wealth of illustrative examples, suggestions, and practical strategies on how to address the challenges arising from the introduction of statistical and probabilistic concepts in pre-school and school curricula.
This collection will inform practices in research and teaching by providing a detailed account of current best practices, challenges, and issues, and of future trends and directions in early statistical and probabilistic learning worldwide. Further, it will contribute to future research and theory building by addressing theoretical, epistemological, and methodological considerations regarding the design of probability and statistics learning environments for young children.
Автор: Edge M D Название: Statistical Thinking from Scratch ISBN: 0198827636 ISBN-13(EAN): 9780198827634 Издательство: Oxford Academ Рейтинг: Цена: 47510.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Focuses on detailed instruction in a single statistical technique, simple linear regression (SLR), with the goal of gaining tools, understanding, and intuition that can be applied to other contexts.
Автор: Donoghue Anthony Название: Statistical Thinking through Media Examples ISBN: 1516565533 ISBN-13(EAN): 9781516565535 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 69350.00 T Наличие на складе: Поставка под заказ. Описание: Statistical Thinking through Media Examples uses real-world examples from various media to give students an introduction to fundamentals of statistical thinking. Unlike many standard texts in the discipline, the book focuses on conceptual understanding – the meaning behind mathematical calculations rather than the calculations themselves. Written in accessible language, the book begins by discussing the importance of learning how to assess the quality of research results presented by the media. This understanding creates an essential context for subsequent chapters on questioning study design including polls and surveys, reasoning with variation in data measurements, understanding probability, confidence intervals, hypothesis testing, and linear regression. Students also learn how statistics can be misused and manipulated by researchers to provide a desired result. The second edition features new coverage of select topics, including ANOVA, Chi-Square tests, and multiple linear regression. Every chapter references online resources or includes in-depth discussion to draw connections between statistical concepts and media examples, such as studies on alcohol consumption and cardiovascular health, American football and brain injury, public mass shootings, dishonesty in scientific research, and more. Statistical Thinking through Media Examples is an ideal resource for any course that deals with introductory statistics, particularly those in the health and social sciences, journalism, and business.
Автор: Tu, Yu-kang Gilthorpe, Mark S. (university Of Leeds, Uk) Название: Statistical thinking in epidemiology ISBN: 0367382555 ISBN-13(EAN): 9780367382551 Издательство: Taylor&Francis Рейтинг: Цена: 65320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
While biomedical researchers may be able to follow instructions in the manuals accompanying the statistical software packages, they do not always have sufficient knowledge to choose the appropriate statistical methods and correctly interpret their results. Statistical Thinking in Epidemiology examines common methodological and statistical problems in the use of correlation and regression in medical and epidemiological research: mathematical coupling, regression to the mean, collinearity, the reversal paradox, and statistical interaction.
Statistical Thinking in Epidemiology is about thinking statistically when looking at problems in epidemiology. The authors focus on several methods and look at them in detail: specific examples in epidemiology illustrate how different model specifications can imply different causal relationships amongst variables, and model interpretation is undertaken with appropriate consideration of the context of implicit or explicit causal relationships. This book is intended for applied statisticians and epidemiologists, but can also be very useful for clinical and applied health researchers who want to have a better understanding of statistical thinking.
Throughout the book, statistical software packages R and Stata are used for general statistical modeling, and Amos and Mplus are used for structural equation modeling.
Автор: Aisling Leavy; Maria Meletiou-Mavrotheris; Efi Pap Название: Statistics in Early Childhood and Primary Education ISBN: 9811345546 ISBN-13(EAN): 9789811345548 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This compilation focuses on the theory and conceptualisation of statistics and probability in the early years and the development of young children’s (ages 3-10) understanding of data and chance. It provides a comprehensive overview of cutting-edge international research on the development of young learners’ reasoning about data and chance in formal, informal, and non-formal educational contexts. The authors share insights into young children’s statistical and probabilistic reasoning and provide early childhood educators and researchers with a wealth of illustrative examples, suggestions, and practical strategies on how to address the challenges arising from the introduction of statistical and probabilistic concepts in pre-school and school curricula.
This collection will inform practices in research and teaching by providing a detailed account of current best practices, challenges, and issues, and of future trends and directions in early statistical and probabilistic learning worldwide. Further, it will contribute to future research and theory building by addressing theoretical, epistemological, and methodological considerations regarding the design of probability and statistics learning environments for young children.
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