Описание: Improve Your Analytical Skills 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.
Описание: Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix. The book presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. References to technical details of the methods are provided for readers who wish to investigate the full theoretical background. All the methods are accompanied with R examples that show how to conduct the analyses. The examples, software, and other materials are available on a supplementary website.
Описание: Through four previous editions, Introductory Statistics has made statistics both interesting and accessible to a wide varied audience. The realistic content of its examples and exercises, the clarity and brevity of its presentation, and the soundness of its pedagogical approach have received the highest remarks from readers. Now this bestseller is available in a new fifth edition technology version!
Автор: Michael J. Crawley Название: Statistics: An Introduction using R ISBN: 0470022973 ISBN-13(EAN): 9780470022979 Издательство: Wiley Рейтинг: Цена: 8085 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.
Автор: Wheelan Charles Название: Naked Statistics: Stripping the Dread from the Data ISBN: 0393071952 ISBN-13(EAN): 9780393071955 Издательство: Wiley Рейтинг: Цена: 2193 р. Наличие на складе: Поставка под заказ.
Описание: The best-selling author of Naked Economics defies the odds with a book about statistics that you`ll welcome and enjoy.
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.
Описание: Remaining the go-to resource for learning how to use SAS for many kinds of statistical analysis, this third edition of a bestseller explains how to conduct a range of statistical analyses using the latest version of SAS. It illustrates each type of analysis with numerous real-world data examples, such as environmental causes of diseases, hypertension treatment, and gastric cancer treatment. This edition presents the new graphics procedures of SAS 9.2. It also includes more end-of-chapter exercises and selected answers in the appendix, along with a solutions manual that provides SAS code, output, and comments. The SAS programs and data sets used in the book are available online.
Автор: Miles J & Banyard P Название: Understanding and Using Statistics in Psychology ISBN: 0761943978 ISBN-13(EAN): 9780761943976 Издательство: Sage Publications Рейтинг: Цена: 4255 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Encourages the reader to understand why a particular test is being used and what the results mean in the context of a psychological study, focusing on meaning and understanding rather than mindless numerical calculation. This book includes real world examples to aid the understanding of why statistics are valuable.
Автор: Miles J & Banyard P Название: Understanding and Using Statistics in Psychology ISBN: 076194396X ISBN-13(EAN): 9780761943969 Издательство: Sage Publications Рейтинг: Цена: 13344 р. Наличие на складе: Поставка под заказ.
Описание: Encourages the reader to understand why a particular test is being used and what the results mean in the context of a psychological study, focusing on meaning and understanding rather than mindless numerical calculation. This book includes real world examples to aid the understanding of why statistics are valuable.
Описание: This text is unique in that it takes an activity-based approach and fully integrates the use of technology. The authors make technology an essential component of the course using the argument that significant and more realistic problems can be investigated using technology, and with technology, students can concentrate on ideas rather than computational details.
Автор: Michael J. Crawley Название: Statistics: An Introduction using R ISBN: 0470022981 ISBN-13(EAN): 9780470022986 Издательство: Wiley Рейтинг: Цена: 3459 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.
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