Joseph R's Books

R in a Nutshell

A Desktop Quick Reference

By: Joseph Adler

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R in a Nutshell

A Desktop Quick Reference

By: Joseph Adler

Why learn R? Because it's rapidly becoming the standard for developing statistical software. R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics. The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems. Understand the basics of the language, including the nature of R objects Learn how to write R functions and build your own packages Work with data through visualization, statistical analysis, and other methods Explore the wealth of packages contributed by the R community Become familiar with the lattice graphics package for high-level data visualization Learn about bioinformatics packages provided by Bioconductor "I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians.

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Page Count

636

Publisher

"O'Reilly Media, Inc."

Published Date

ISBN 10

1449383041

ISBN 13

9781449383046

R in a Nutshell

By: Joseph Adler (M.Eng.)

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R in a Nutshell

By: Joseph Adler (M.Eng.)

If you're considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You'll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports. Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop. Get started quickly with an R tutorial and hundreds of examples Explore R syntax, objects, and other language details Find thousands of user-contributed R packages online, including Bioconductor Learn how to use R to prepare data for analysis Visualize your data with R's graphics, lattice, and ggplot2 packages Use R to calculate statistical fests, fit models, and compute probability distributions Speed up intensive computations by writing parallel R programs for Hadoop Get a complete desktop reference to R.

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722

Publisher

"O'Reilly Media, Inc."

Published Date

ISBN 10

1449358233

ISBN 13

9781449358235

R for Stata Users

By: Robert A. Muenchen,Joseph M. Hilbe

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R for Stata Users

By: Robert A. Muenchen,Joseph M. Hilbe

Stata is the most flexible and extensible data analysis package available from a commercial vendor. R is a similarly flexible free and open source package for data analysis, with over 3,000 add-on packages available. This book shows you how to extend the power of Stata through the use of R. It introduces R using Stata terminology with which you are already familiar. It steps through more than 30 programs written in both languages, comparing and contrasting the two packages' different approaches. When finished, you will be able to use R in conjunction with Stata, or separately, to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses. A glossary defines over 50 R terms using Stata jargon and again using more formal R terminology. The table of contents and index allow you to find equivalent R functions by looking up Stata commands and vice versa. The example programs and practice datasets for both R and Stata are available for download.

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Page Count

549

Publisher

Springer Science & Business Media

Published Date

ISBN 10

1441913181

ISBN 13

9781441913180

R Projects For Dummies

By: Joseph Schmuller

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R Projects For Dummies

By: Joseph Schmuller

Make the most of R’s extensive toolset R Projects For Dummies offers a unique learn-by-doing approach. You will increase the depth and breadth of your R skillset by completing a wide variety of projects. By using R’s graphics, interactive, and machine learning tools, you’ll learn to apply R’s extensive capabilities in an array of scenarios. The depth of the project experience is unmatched by any other content online or in print. And you just might increase your statistics knowledge along the way, too! R is a free tool, and it’s the basis of a huge amount of work in data science. It's taking the place of costly statistical software that sometimes takes a long time to learn. One reason is that you can use just a few R commands to create sophisticated analyses. Another is that easy-to-learn R graphics enable you make the results of those analyses available to a wide audience. This book will help you sharpen your skills by applying them in the context of projects with R, including dashboards, image processing, data reduction, mapping, and more. Appropriate for R users at all levels Helps R programmers plan and complete their own projects Focuses on R functions and packages Shows how to carry out complex analyses by just entering a few commands If you’re brand new to R or just want to brush up on your skills, R Projects For Dummies will help you complete your projects with ease.

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Page Count

384

Publisher

John Wiley & Sons

Published Date

ISBN 10

1119446171

ISBN 13

9781119446170

Statistical Analysis with R For Dummies

By: Joseph Schmuller

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Statistical Analysis with R For Dummies

By: Joseph Schmuller

Understanding the world of R programming and analysis has never been easier Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming. People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results. Gets you up to speed on the #1 analytics/data science software tool Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling Shows you how R offers intel from leading researchers in data science, free of charge Provides information on using R Studio to work with R Get ready to use R to crunch and analyze your data—the fast and easy way!

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Page Count

480

Publisher

John Wiley & Sons

Published Date

ISBN 10

1119337267

ISBN 13

9781119337263

A Guide to R for Social and Behavioral Science Statistics

By: Brian Joseph Gillespie,Kathleen Charli Hibbert,William E. Wagner, III

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A Guide to R for Social and Behavioral Science Statistics

By: Brian Joseph Gillespie,Kathleen Charli Hibbert,William E. Wagner, III

A Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R. This handy guide contains basic information on statistics for undergraduates and graduate students, shown in the R statistical language using RStudio®. The book is geared toward social and behavioral science statistics students, especially those with no background in computer science. Written as a companion book to be used alongside a larger introductory statistics text, the text follows the most common progression of statistics for social scientists. The guide also serves as a companion for conducting data analysis in a research methods course or as a stand-alone R and statistics text. This guide can teach anyone how to use R to analyze data, and uses frequent reminders of basic statistical concepts to accompany instructions in R to help walk students through the basics of learning how to use R for statistics.

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Page Count

268

Publisher

SAGE Publications

Published Date

ISBN 10

1544344007

ISBN 13

9781544344003

Nonparametric Statistical Methods Using R

By: John Kloke,Joseph W. McKean

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Nonparametric Statistical Methods Using R

By: John Kloke,Joseph W. McKean

A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R.

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Page Count

283

Publisher

CRC Press

Published Date

ISBN 10

1439873445

ISBN 13

9781439873441

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R

A Workbook

By: Joseph F. Hair Jr.,G. Tomas M. Hult,Christian M. Ringle,Marko Sarstedt,Nicholas P. Danks,Soumya Ray

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Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R

A Workbook

By: Joseph F. Hair Jr.,G. Tomas M. Hult,Christian M. Ringle,Marko Sarstedt,Nicholas P. Danks,Soumya Ray

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.

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Page Count

208

Publisher

Springer Nature

Published Date

ISBN 10

3030805190

ISBN 13

9783030805197

An Introduction to Homological Algebra

By: Joseph J. Rotman

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An Introduction to Homological Algebra

By: Joseph J. Rotman

Graduate mathematics students will find this book an easy-to-follow, step-by-step guide to the subject. Rotman’s book gives a treatment of homological algebra which approaches the subject in terms of its origins in algebraic topology. In this new edition the book has been updated and revised throughout and new material on sheaves and cup products has been added. The author has also included material about homotopical algebra, alias K-theory. Learning homological algebra is a two-stage affair. First, one must learn the language of Ext and Tor. Second, one must be able to compute these things with spectral sequences. Here is a work that combines the two.

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722

Publisher

Springer Science & Business Media

Published Date

ISBN 10

0387683240

ISBN 13

9780387683249

Book's by Joseph R

R in a Nutshell

R in a Nutshell

R in a Nutshell

R in a Nutshell

R for Stata Users

R for Stata Users

R Projects For Dummies

R Projects For Dummies

Statistical Analysis with R For Dummies

Statistical Analysis with R For Dummies

A Guide to R for Social and Behavioral Science Statistics

A Guide to R for Social and Behavioral Science Statistics

Nonparametric Statistical Methods Using R

Nonparametric Statistical Methods Using R

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R

An Introduction to Homological Algebra

An Introduction to Homological Algebra

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