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A First Course in Statistical Programming with R

3rd Edition


  • Date Published: May 2021
  • availability: In stock
  • format: Paperback
  • isbn: 9781108995146

£ 34.99

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About the Authors
  • 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 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.

    • 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: May 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

  • Authors

    W. John Braun, University of British Columbia
    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, University of Western Ontario
    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.

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