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Statistics: An Introduction using R, Michael J. Crawley



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Цена: 3130р.
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Автор: Michael J. Crawley
Название:  Statistics: An Introduction using R   (Майкл Краули: Статистические методы)
Издательство: Wiley
Классификация:
Вероятность и статистика

ISBN: 0470022981
ISBN-13(EAN): 9780470022986
ISBN: 0-470-02298-1
ISBN-13(EAN): 978-0-470-02298-6
Обложка/Формат: Paperback
Страницы: 342
Вес: 0.57 кг.
Дата издания: 11.03.2005
Язык: ENG
Иллюстрации: Illustrations
Размер: 24.28 x 16.97 x 1.98 cm
Читательская аудитория: Professional & vocational
Подзаголовок: An introduction using r
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Англии
Описание: Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the authors previous best-selling title Statistical Computing.
*Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology.
*Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data.
*The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing.
*Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.
*Includes numerous worked examples and exercises within each chapter.
Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

Дополнительное описание: Кол-во стр.: 342
Формат: 246 x 170
Дата издания: 2005
Вес: 650
Круг читателей: academic, specialist; research, professional





An Introduction to Multivariate Statistical Analysis, Third Edition

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
Рейтинг:
Цена: 16093 р.
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.

Introduction To Probability And Statistics For Engineers And Scie

Автор: Ross
Название: Introduction To Probability And Statistics For Engineers And Scie
ISBN: 0125984723 ISBN-13(EAN): 9780125984720
Издательство: Elsevier Science
Цена: 8691 р.
Наличие на складе: Невозможна поставка.

An Introduction to Survival Analysis Using Stata, Revised Third Edition

Автор: Cleves
Название: An Introduction to Survival Analysis Using Stata, Revised Third Edition
ISBN: 1597181749 ISBN-13(EAN): 9781597181747
Издательство: Taylor&Francis
Рейтинг:
Цена: 7732 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: An Introduction to Survival Analysis Using Stata, Revised Third Edition is the ideal tutorial for professional data analysts who want to learn survival analysis for the first time or who are well versed in survival analysis but are not as dexterous in using Stata to analyze survival data. This text also serves as a valuable reference to those readers who already have experience using Stata’s survival analysis routines. The revised third edition has been updated for Stata 14, and it includes a new section on predictive margins and marginal effects, which demonstrates how to obtain and visualize marginal predictions and marginal effects using the margins and marginsplot commands after survival regression models. Survival analysis is a field of its own that requires specialized data management and analysis procedures. To meet this requirement, Stata provides the st family of commands for organizing and summarizing survival data. This book provides statistical theory, step-by-step procedures for analyzing survival data, an in-depth usage guide for Stata's most widely used st commands, and a collection of tips for using Stata to analyze survival data and to present the results. This book develops from first principles the statistical concepts unique to survival data and assumes only a knowledge of basic probability and statistics and a working knowledge of Stata. The first three chapters of the text cover basic theoretical concepts: hazard functions, cumulative hazard functions, and their interpretations; survivor functions; hazard models; and a comparison of nonparametric, semiparametric, and parametric methodologies. Chapter 4 deals with censoring and truncation. The next three chapters cover the formatting, manipulation, stsetting, and error checking involved in preparing survival data for analysis using Stata's st analysis commands. Chapter 8 covers nonparametric methods, including the Kaplan–Meier and Nelson–Aalen estimators and the various nonparametric tests for the equality of survival experience. Chapters 9–11 discuss Cox regression and include various examples of fitting a Cox model, obtaining predictions, interpreting results, building models, model diagnostics, and regression with survey data. The next four chapters cover parametric models, which are fit using Stata's streg command. These chapters include detailed derivations of all six parametric models currently supported in Stata and methods for determining which model is appropriate, as well as information on stratification, obtaining predictions, and advanced topics such as frailty models. Chapter 16 is devoted to power and sample-size calculations for survival studies. The final chapter covers survival analysis in the presence of competing risks.

Introduction to Nonparametric Statistics for the Biological Sciences Using R

Автор: MacFarland
Название: Introduction to Nonparametric Statistics for the Biological Sciences Using R
ISBN: 3319306332 ISBN-13(EAN): 9783319306339
Издательство: Springer
Рейтинг:
Цена: 6264 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book contains a rich set of tools for nonparametric analyses, and the purpose of this supplemental text is to provide guidance to students and professional researchers onhow R is used for nonparametric data analysis in the biological sciences:To introduce when nonparametricapproaches to data analysis are appropriateTo introduce the leadingnonparametric tests commonly used in biostatistics and how R is used togenerate appropriate statistics for each testTo introduce common figurestypically associated with nonparametric data analysis and how R is used togenerate appropriate figures in support of each data setThe book focuses on how R is used todistinguish between data that could be classified as nonparametric as opposedto data that could be classified as parametric, with both approaches to data classification covered extensively.Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses and tests using R to broadly compare differences between data sets and statistical approach.This supplemental text is intended for:Upper-level undergraduate and graduate students majoring in the biological sciences, specifically those in agriculture, biology, and health science - both students in lecture-type courses and also those engaged in research projects, such as a master's thesis or a doctoral dissertationAnd biological researchers at the professional level without a nonparametric statistics background but who regularly work with data more suitable to a nonparametric approach to data analysis

Basic statistics: introduction to statistics using megastat and excel

Автор: Orris
Название: Basic statistics: introduction to statistics using megastat and excel
ISBN: 0071254315 ISBN-13(EAN): 9780071254311
Издательство: McGraw-Hill
Рейтинг:
Цена: 3656 р.
Наличие на складе: Поставка под заказ.

Описание: Offers an Excel-focused approach to using statistics in business. This work illustrates statistical concepts with applied examples. It introduces modern computing tools and applications, and presents statistical concepts as applied using Excel. It also enables students to take advantage of Excel to develop and drive problem-solving skills.

Basic statistics: introduction to statistics using megastat and excel with cd

Автор: Orris
Название: Basic statistics: introduction to statistics using megastat and excel with cd
ISBN: 0073211583 ISBN-13(EAN): 9780073211589
Издательство: McGraw-Hill
Цена: 6791 р.
Наличие на складе: Поставка под заказ.

Описание: Offers an Excel-focused approach to using statistics in business. This work illustrates statistical concepts with applied examples immediately upon introduction. It introduces modern computing tools and applications, and focuses on presenting statistical concepts as applied using Excel, enhanced by MegaStat, the Excel add-in.

Introduction To The Theory of Statistics

Автор: Mood
Название: Introduction To The Theory of Statistics
ISBN: 0070854653 ISBN-13(EAN): 9780070854659
Издательство: McGraw-Hill
Рейтинг:
Цена: 5224 р.
Наличие на складе: Невозможна поставка.

Описание: A self contained introduction to classical statistical theory. The material is suitable for students who have successfully completed a single year`s course in calculus with no prior knowledge of statistics or probability. Third revised edition.

Introduction To Probability And Statistics: Principles And Applications For Engineering And The Computing Sciences

Автор: Milton; Arnold
Название: Introduction To Probability And Statistics: Principles And Applications For Engineering And The Computing Sciences
ISBN: 0071198598 ISBN-13(EAN): 9780071198592
Издательство: McGraw-Hill
Рейтинг:
Цена: 4598 р.
Наличие на складе: Поставка под заказ.

Описание: Designed for the first course in probability and statistics taken by students majoring in engineering and the computing sciences, this text offers a presentation of applications and theory. It aims to develop the theoretical foundations for the statistical methods. It explores the practical implications of the formal results to problem-solving.

Statistics: An Introduction using R

Автор: Michael J. Crawley
Название: Statistics: An Introduction using R
ISBN: 0470022973 ISBN-13(EAN): 9780470022979
Издательство: Wiley
Рейтинг:
Цена: 7315 р.
Наличие на складе: Поставка под заказ.

Описание: Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing.
*Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology.
*Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data.
*The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing.
*Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.
*Includes numerous worked examples and exercises within each chapter.
Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

An Introduction to Medical Statistics 4th Edition

Автор: Bland Martin
Название: An Introduction to Medical Statistics 4th Edition
ISBN: 0199589925 ISBN-13(EAN): 9780199589920
Издательство: Oxford Academ
Рейтинг:
Цена: 3173 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: An Introduction to Medical Statistics, fourth edition, is a `must-have` textbook. Written in an easy-to-understand style and packed with real life examples, the text clearly explains the common statistical methods seen in published research and guidelines, as well as how to interpret and analyse statistics for clinical practice.

Introduction to Statistics for Forensic Scientists

Автор: David Lucy
Название: Introduction to Statistics for Forensic Scientists
ISBN: 0470022019 ISBN-13(EAN): 9780470022016
Издательство: Wiley
Рейтинг:
Цена: 4180 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Introduction to Statistics for Forensic Scientists is an essential introduction to the subject, gently guiding the reader through the key statistical techniques used to evaluate various types of forensic evidence. Assuming only a modest mathematical background, the book uses real-life examples from the forensic science literature and forensic case-work to illustrate relevant statistical concepts and methods.
Opening with a brief overview of the history and use of statistics within forensic science, the text then goes on to introduce statistical techniques commonly used to examine data obtained during laboratory experiments. There is a strong emphasis on the evaluation of scientific observation as evidence and modern Bayesian approaches to interpreting forensic data for the courts. The analysis of key forms of evidence are discussed throughout with a particular focus on DNA, fibres and glass.
An invaluable introduction to the statistical interpretion of forensic evidence; this book will be invaluable for all undergraduates taking courses in forensic science.
*Introduction to the key statistical techniques used in the evaluation of forensic evidence
*Includes end of chapter exercises to enhance student understanding
*Numerous examples taken from forensic science to put the subject into context

Introduction to Statistics for Forensic Scientists

Автор: David Lucy
Название: Introduction to Statistics for Forensic Scientists
ISBN: 0470022000 ISBN-13(EAN): 9780470022009
Издательство: Wiley
Рейтинг:
Цена: 13481 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Introduction to Statistics for Forensic Scientists is an essential introduction to the subject, gently guiding the reader through the key statistical techniques used to evaluate various types of forensic evidence. Assuming only a modest mathematical background, the book uses real-life examples from the forensic science literature and forensic case-work to illustrate relevant statistical concepts and methods.
Opening with a brief overview of the history and use of statistics within forensic science, the text then goes on to introduce statistical techniques commonly used to examine data obtained during laboratory experiments. There is a strong emphasis on the evaluation of scientific observation as evidence and modern Bayesian approaches to interpreting forensic data for the courts. The analysis of key forms of evidence are discussed throughout with a particular focus on DNA, fibres and glass.
An invaluable introduction to the statistical interpretation of forensic evidence; this book will be invaluable for all undergraduates taking courses in forensic science.
*Introduction to the key statistical techniques used in the evaluation of forensic evidence
*Includes end of chapter exercises to enhance student understanding
*Numerous examples taken from forensic science to put the subject into context


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