164,33 €
182,59 €
-10% with code: EXTRA
Using R for Introductory Statistics
Using R for Introductory Statistics
164,33
182,59 €
  • We will send in 10–14 business days.
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 id…
  • Publisher:
  • Year: 2014
  • Pages: 518
  • ISBN-10: 1466590734
  • ISBN-13: 9781466590731
  • Format: 15.2 x 23.1 x 2.3 cm, hardcover
  • Language: English
  • SAVE -10% with code: EXTRA

Using R for Introductory Statistics (e-book) (used book) | bookbook.eu

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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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  • Author: John Verzani
  • Publisher:
  • Year: 2014
  • Pages: 518
  • ISBN-10: 1466590734
  • ISBN-13: 9781466590731
  • Format: 15.2 x 23.1 x 2.3 cm, hardcover
  • Language: English English

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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