Local cover image
Local cover image
Amazon cover image
Image from Amazon.com
Image from Google Jackets
Image from OpenLibrary
See Baker & Taylor
Image from Baker & Taylor

Modern data science with R /by Benjamin S. Baumer, Daniel T. Kaplan and Nicholas J. Horton

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Boca Raton : CRC press, 2025.Edition: 2nd edDescription: xvii, 631 p. : ill. : 25 cmISBN:
  • 9781032941677
Subject(s): Other classification:
  • B28,92R Q7;R5
Summary: Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling statistical questions. Contemporary data science requires a tight integration of knowledge from statistics, computer science, mathematics, and a domain of application. This book will help readers with some background in statistics and modest prior experience with coding develop and practice the appropriate skills to tackle complex data science projects. The book features a number of exercises and has a flexible organization conducive to teaching a variety of semester courses.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Home library Call number Status Barcode
Textual Textual Central Science Library Central Science Library B28, 92R Q7;R5 (Browse shelf(Opens below)) Available SL1655954

Includes Appendices, Bibliography and indices

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling statistical questions. Contemporary data science requires a tight integration of knowledge from statistics, computer science, mathematics, and a domain of application. This book will help readers with some background in statistics and modest prior experience with coding develop and practice the appropriate skills to tackle complex data science projects. The book features a number of exercises and has a flexible organization conducive to teaching a variety of semester courses.

There are no comments on this title.

to post a comment.

Click on an image to view it in the image viewer

Local cover image