Exploring Data Science with R and the Tidyverse: A Concise Introduction

This book teaches data science using R and the tidyverse, with no prior knowledge required in programming or mathematics. It is self-contained and targeted for undergraduate students, but also applicable to graduate students and beyond. It develops concepts using real-world examples and provides an accompanying R package for further practice.

Format: Hardback
Length: 476 pages
Publication date: 14 August 2023
Publisher: Taylor & Francis Ltd

This comprehensive book serves as an invaluable guide for beginners embarking on their journey into the realm of data science, utilizing the powerful R programming language and the versatile tidyverse framework. With no prior knowledge in college-level programming or mathematics, such as calculus or statistics, readers can confidently dive into the world of data science without the need for extensive external resources for onboarding. The book's self-contained nature allows readers to immediately begin building data science workflows, fostering a seamless learning experience. While the contents are tailored specifically for undergraduate students, they are equally relevant and valuable to students at the graduate level and beyond.

To effectively convey the concepts, the book employs a rich array of real-world examples, captivating the reader and motivating them to grasp the intricacies of data science. By the conclusion of the text, readers will possess a solid foundation in R programming, adeptly loading and manipulating data frames using tidyverse tools, conducting statistical analyses, and drawing meaningful inferences from the data. Furthermore, they will be capable of performing modeling from both numerical and textual data, generating data visualizations using ggplot2, and comprehending the visual representations presented.

In addition to the textbook, an accompanying R package named edsdata is provided, containing a wealth of synthetic and real datasets utilized throughout the book. These datasets serve as valuable resources for further practice, allowing readers to deepen their understanding and reinforce their learning. An exercise set is also made available, meticulously designed to be compatible with automated grading tools for instructors. This exercise set empowers instructors to assess student comprehension and provide timely feedback, enhancing the learning process and fostering a deeper understanding of the subject matter.

In summary, this book is a must-have for anyone seeking to embark on a data science career, providing a comprehensive and accessible introduction to the field. With its clear and concise writing style, real-world examples, and practical exercises, it equips readers with the skills and knowledge necessary to thrive in the rapidly evolving world of data analysis and visualization. Whether you are a student, professional, or simply interested in exploring the vast potential of data, this book is your gateway to a world of endless possibilities.

Dimension: 254 x 178 (mm)
ISBN-13: 9781032329505