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      Book

      Using R for Introductory Statistics
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      Book

      Using R for Introductory Statistics

      DOI link for Using R for Introductory Statistics

      Using R for Introductory Statistics book

      Using R for Introductory Statistics

      DOI link for Using R for Introductory Statistics

      Using R for Introductory Statistics book

      ByJohn Verzani
      Edition 2nd Edition
      First Published 2014
      eBook Published 12 December 2018
      Pub. Location New York
      Imprint Chapman and Hall/CRC
      DOI https://doi.org/10.1201/9781315373089
      Pages 518
      eBook ISBN 9781315373089
      Subjects Mathematics & Statistics
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      Verzani, J. (2014). Using R for Introductory Statistics (2nd ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781315373089

      ABSTRACT

      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.

      TABLE OF CONTENTS

      chapter 1|19 pages

      Getting started

      chapter 2|68 pages

      Univariate data

      chapter 3|25 pages

      Bivariate data

      chapter 4|39 pages

      Multivariate data

      chapter 5|22 pages

      Multivariate graphics

      chapter 6|31 pages

      Populations

      chapter 7|20 pages

      Statistical inference

      chapter 8|32 pages

      Confidence intervals

      chapter 9|40 pages

      Significance tests

      chapter 10|30 pages

      Goodness of fit

      chapter 11|9 pages

      Linear regression

      chapter 12|36 pages

      Analysis of variance

      chapter 13|18 pages

      Extensions of the linear model

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