Modern Data Science with R

by Benjamin S. Baumer

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.

Genres: Computer Science

582 pages, Kindle Edition

Published March 16, 2017

Reviews

[Duncan McKinnon · Rating 5 out of 5]

Great long term reference. Touches briefly on a lot of material and very up to date on R. Good starting point for deeper dives into different areas. Some of the syntactic choices were a little questionable, but everything worked. Used this in my intro to DS course for an MS in Applied Computational Mathematics and Statistics.

[Mills College Library]

006.312 B3479 2017