Powlect W/Exmvw Elem Statistic:Looking At The Big Picture, Pfenning
Автор: Efron Название: An Introduction to the Bootstrap ISBN: 0412042312 ISBN-13(EAN): 9780412042317 Издательство: Taylor&Francis Рейтинг: Цена: 22968.00 р. 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.
Автор: Tussy/Gustafson Название: Powlect W/Exmvw Elem & Intermed Algebra ISBN: 1111988242 ISBN-13(EAN): 9781111988241 Издательство: Cengage Learning Рейтинг: Цена: 7602.00 р. Наличие на складе: Нет в наличии.
Автор: Olafsen Название: Sturge`S Statistical And Thermal Ph ISBN: 1482256002 ISBN-13(EAN): 9781482256000 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Поставка под заказ.
Описание: This fully revised and updated edition provides a uniquely accessible introduction to the principles and applications of statistical mechanics and thermodynamics. Based on the highly acclaimed text by famous physicist M.D. Sturge, it continues its emphasis on explaining concepts with simple mathematics and plain English.
Автор: Cohen/Lee/Sklar Название: Powlect W/Exmvw Precalculus ISBN: 1111428794 ISBN-13(EAN): 9781111428792 Издательство: Cengage Learning Рейтинг: Цена: 9502.00 р. Наличие на складе: Нет в наличии.
Автор: Gould, William Название: The Mata book ISBN: 159718263X ISBN-13(EAN): 9781597182638 Издательство: Taylor&Francis Рейтинг: Цена: 9186.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Mata Book: A Book for Serious Programmers and Those Who Want to Be is the book that Stata programmers have been waiting for. Mata is a serious programming language for developing small- and large-scale projects and for adding features to Stata.
Автор: Moulin Pierre Название: Statistical Inference for Engineers and Data Scientists ISBN: 1107185920 ISBN-13(EAN): 9781107185920 Издательство: Cambridge Academ Рейтинг: Цена: 10138.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An up-to-date and mathematically accessible introduction to the tools needed to address modern inference problems in engineering and data science. Richly illustrated with examples and exercises connecting the theory with practice, it is the `go to` guide for students studying the topic, and an excellent reference for researchers and practitioners.
Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.
New to the Second Edition
The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows
New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics
New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping
New chapter on simulation that includes examples of data generated from complex models and distributions
A detailed discussion of the philosophy and use of the knitr and markdown packages for R
New packages that extend the functionality of R and facilitate sophisticated analyses
Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots
Easily Find Your Desired Task
Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.
Автор: Johnson/Kuby Название: Internal Exmvw Elem Statistics ISBN: 0840053916 ISBN-13(EAN): 9780840053916 Издательство: Cengage Learning Рейтинг: Цена: 7918.00 р. Наличие на складе: Нет в наличии.
Описание: This book presents the proceedings of the 2nd Pacific Rim Statistical Conference for Production Engineering: Production Engineering, Big Data and Statistics, which took place at Seoul National University in Seoul, Korea in December, 2016.
Автор: Wainwright Martin J Название: Cambridge Series in Statistical and Probabilistic Mathematic ISBN: 1108498027 ISBN-13(EAN): 9781108498029 Издательство: Cambridge Academ Рейтинг: Цена: 10771.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent years have seen an explosion in the volume and variety of data collected in scientific disciplines from astronomy to genetics and industrial settings ranging from Amazon to Uber. This graduate text equips readers in statistics, machine learning, and related fields to understand, apply, and adapt modern methods suited to large-scale data.
Автор: Donoghue Anthony Название: Statistical Thinking through Media Examples ISBN: 1516565533 ISBN-13(EAN): 9781516565535 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 10402.00 р. Наличие на складе: Нет в наличии.
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.
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