Using R for Introductory Statistics

Using R for Introductory Statistics ebook complet au format Pdf, ePub et Kindle. Using R for Introductory Statistics de John Verzani, publié par CRC Press le 2018-10-03 avec 576 pages. Using R for Introductory Statistics est l'un des livres populaires de Computers parmi de nombreux autres livres complets sur amazon kindle illimité, cliquez sur Obtenir un livre pour commencer à lire et télécharger des livres en ligne gratuitement dès maintenant. Obtenez plus d'avantages avec l'essai gratuit Kindle Unlimited, vous pouvez lire autant de livres que vous le souhaitez maintenant.

  • Using R for Introductory Statistics

  • Auteur : John Verzani
  • Editeur : CRC Press
  • Isbn Code : 1315362678
  • Genre : Computers
  • Nombre de pages : 518
  • Date de publication : 2018-10-03
  • Évaluation des livres 4.5
    Par 38 lecteurs

The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.

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