A First Course in Statistical Programming with R (Paperback)

W. John Braun

ISBN 10: 1108995144 / ISBN 13: 9781108995146

Published by Cambridge University Press, Cambridge, 2021

About this Item

Paperback. This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded coverage of ggplot2, and R Markdown. The expanded simulation chapter introduces the BoxMuller and MetropolisHastings algorithms. New examples and exercises have been added throughout. This is the only introduction you'll need to start programming in R, the computing standard for analyzing data. This book comes with real R code that teaches the standards of the language. Unlike other introductory books on the R system, this book emphasizes portable programming skills that apply to most computing languages and techniques used to develop more complex projects. Solutions, datasets, and any errata are available from ce. Worked examples - from real applications - hundreds of exercises, and downloadable code, datasets, and solutions make a complete package for anyone working in or learning practical data science. This book is for students who are learning computing to use in data science and scientific applications. It takes the reader from basic principles of computing to numerical methods, using the R programming language. Worked examples, hundreds of exercises, and downloadable code, datasets, and solutions make a complete package. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781108995146

Bibliographic Details

• Title: A First Course in Statistical Programming with R (Paperback)
• Publisher: Cambridge University Press, Cambridge
• Publication Date: 2021
• Language: English
• ISBN 10: 1108995144
• ISBN 13: 9781108995146
• Binding: Paperback
• Edition: 3rd Edition
• Condition: new

About this title

Synopsis

This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded coverage of ggplot2, and R Markdown. The expanded simulation chapter introduces the Box–Muller and Metropolis–Hastings algorithms. New examples and exercises have been added throughout. This is the only introduction you'll need to start programming in R, the computing standard for analyzing data. This book comes with real R code that teaches the standards of the language. Unlike other introductory books on the R system, this book emphasizes portable programming skills that apply to most computing languages and techniques used to develop more complex projects. Solutions, datasets, and any errata are available from www.statprogr.science. Worked examples - from real applications - hundreds of exercises, and downloadable code, datasets, and solutions make a complete package for anyone working in or learning practical data science.

About the Authors

W. John Braun is Professor of Statistics at UBC's Okanagan campus. His research interests are in the modeling of environmental phenomena, such as wildfire, as well as statistical education, particularly as it relates to the R programming language.

Duncan J. Murdoch is a Professor Emeritus and was a member of the R Core Team of developers and co-president of the R Foundation. He is one of the developers of the rgl package for 3D visualization in R, and has also developed numerous other R packages.