A First Course in Statistical Programming with R
3rd Edition
$44.99 (P)
- Authors:
- W. John Braun, University of British Columbia
- Duncan J. Murdoch, University of Western Ontario
- Date Published: July 2021
- availability: In stock
- format: Paperback
- isbn: 9781108995146
$
44.99
(P)
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 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.
Read more- Self-contained and accessible to anyone familiar with university-level calculus
- The basics of R syntax, statistical graphics, and the tidyverse are explained with real R code
- Programming ideas, including good, efficient style and debugging, are introduced
- Applications in simulation and optimization as well as numerical linear algebra are discussed
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×Product details
- Edition: 3rd Edition
- Date Published: July 2021
- format: Paperback
- isbn: 9781108995146
- length: 280 pages
- dimensions: 245 x 188 x 15 mm
- weight: 0.6kg
- availability: In stock
Table of Contents
1. Getting Started
2. Introduction to the R Language
3. Programming Statistical Graphics
4. Programming with R
5. Complex Programming in the Tidyverse
6. Simulation
7. Computational Linear Algebra
8. Numerical Optimization
A. Review of Random Variables and Distributions
B. Base Graphics Details
Index.-
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A First Course in Statistical Programming with R
W. John Braun, Duncan J. Murdoch
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