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A First Course in Statistical Programming with R

A First Course in Statistical Programming with R

A First Course in Statistical Programming with R
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A First Course in Statistical Programming with R Paperback - 2021

by Braun, W. John

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Cambridge University Press, 7/8/2021 12:00:01 AM. paperback. Good. 0.7874 9.5669 7.4409.
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Details

  • Title A First Course in Statistical Programming with R
  • Author Braun, W. John
  • Binding Paperback
  • Condition Used - Good
  • Pages 280
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press
  • Publication date 7/8/2021 12:00:01 AM
  • Features Index
  • Bookseller's Inventory # mon0003997136
  • ISBN 9781108995146 / 1108995144
  • Weight 1.3 lbs (0.59 kg)
  • Dimensions 9.5 x 7.8 x 0.5 in (24.13 x 19.81 x 1.27 cm)
  • Size 0.7874 9.5669 7.4409
  • Category Mathematics
  • Library of Congress subjects Statistics, Statistics - Data processing
  • Dewey Decimal Code 519.502
  • Quantity available 1
  • Bookseller catalogues Book

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Reader reviews for A First Course in Statistical Programming with R

From the publisher

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.
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