Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
Language: English
Published by Taylor & Francis Ltd, 2019
- Softcover
- Used

Seller: World of Books Inc, Montgomery, IL, U.S.A.World of Books Inc
AbeBooks seller since March 23, 2026
Condition: Used - Good
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Add to basketItem description from seller
This is a modern textbook in statistical inference, using the principles of data science through R and the Tidyverse. It assumes minimal background knowledge of the reader: there is no algebra, no calculus, and no prior programming/coding experience.
Seller Inventory # CIN0367409828G
- Title
- Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
- Author
- Michael Clifford
- Publisher
- Taylor & Francis Ltd
- Publication year
- 2019
- Condition
- Good
- Binding
- Paperback
- Language
- English
- ISBN 10
- 0367409828
- ISBN 13
- 9780367409821
- Series
- Book 52 of 73: Chapman & Hall/CRC The R
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout.
Features:
● Assumes minimal prerequisites, notably, no prior calculus nor coding experience
● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com
● Centers on simulation-based approaches to statistical inference rather than mathematical formulas
● Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods
● Provides all code and output embedded directly in the text; also available in the online version at moderndive.com
This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels.
"Synopsis" may belong to another edition of this title.
About the Author
• Chester Ismay is a Data Science Evangelist for DataRobot and is based in Portland, Oregon, USA.
•Albert Y. Kim is an Assistant Professor of Statistical and Data Sciences at Smith College in Northampton, Massachusetts, USA.
"About the title" may belong to another edition of this title.
World of Books Inc
Montgomery, IL, U.S.A.
AbeBooks seller since March 23, 2026
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