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Using R for Introductory Statistics

List Price: $89.99
SKU:
9781466590731
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  • Product Details

    Author:
    John Verzani
    Format:
    Hardcover
    Pages:
    518
    Publisher:
    CRC Press (June 26, 2014)
    Language:
    English
    ISBN-13:
    9781466590731
    Weight:
    39.625oz
    Dimensions:
    6.125" x 9.1875"
    File:
    TAYLORFRANCIS-TayFran_260405043548125-20260405.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $89.99
    Series:
    Chapman & Hall/CRC The R Series
    Case Pack:
    10
    As low as:
    $85.49
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Country of Origin:
    United States
    Pub Discount:
    30
    Imprint:
    Chapman and Hall/CRC
  • Overview

    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.