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{ "item_title" : "R by Example", "item_author" : [" Jim Albert", "Maria Rizzo "], "item_description" : "Now in its second edition, R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data.The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, it is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data, and this book is intended to be a useful resource for learning how to implement these procedures in R.The new edition includes updated and expanded coverage of Rstudio, knitr, ggplot2, and text mining, as well as a new chapter on data frames.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/03/176/073/3031760735_b.jpg", "price_data" : { "retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
R by Example|Jim Albert

R by Example

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Overview

Now in its second edition, R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data.

The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, it is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data, and this book is intended to be a useful resource for learning how to implement these procedures in R.

The new edition includes updated and expanded coverage of Rstudio, knitr, ggplot2, and text mining, as well as a new chapter on data frames.

This item is Non-Returnable

Details

  • ISBN-13: 9783031760730
  • ISBN-10: 3031760735
  • Publisher: Springer
  • Publish Date: December 2024
  • Dimensions: 9.21 x 6.14 x 0.95 inches
  • Shipping Weight: 1.44 pounds
  • Page Count: 454

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