Modern Data Science with R 1st Edition

Check out Monetary establishment for Modern Data Science with R 1st Edition

Modern Data Science with R is a comprehensive data science textbook for undergraduates that integrates statistical and computational thinking to solve real-world problems using data. Instead of focusing solely on case studies or programming syntax, this book demonstrates how statistical programming in the state-of-the-art R/RStudio computing environment can be utilized to extract valuable insights from various data sets in order to address pertinent statistical inquiries.

Up-to-date data science necessitates a solid amalgamation of information from statistics, computer science, mathematics, and a field of application. This textbook will assist readers with a basic background in statistics and some prior coding experience to cultivate and implement the necessary skills to tackle complex data science projects. The book includes numerous exercises and is structured in a versatile manner suitable for teaching a variety of semester courses.

Regarding the Authors

– Benjamin S. Baumer: An assistant professor in the Statistical & Data Sciences program at Smith College. With an extensive teaching career as a data scientist, he joined New York Mets as the first full-time statistical analyst in 2004. Co-author of *The Sabermetric Revolution*, he was honored with the 2016 Updated Baseball Analysis Award from the Society for American Baseball Research.

– Daniel T. Kaplan: The DeWitt Wallace professor of mathematics and computer science at Macalester College. He has authored numerous textbooks on statistical modeling and computing and received the 2006 Macalester Excellence in Teaching award.

– Nicholas J. Horton: A professor of statistics at Amherst College. A Fellow of the American Statistical Association (ASA) and member of the NRC Committee on Applied and Theoretical Statistics, he has garnered several national teaching accolades. Author of a series of books on statistical computing, he actively contributes to curricular reform advocating for data-centric thinking among students.

**ISBN-10:** 9781498724487
**ISBN-13:** 978-1498724487

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## FAQ

**1. Who is the target audience for *Modern Data Science with R*?**
*Modern Data Science with R* is aimed at undergraduate students with a background in statistics and some coding experience who are looking to enhance their data science skills.

**2. Does this book cover both statistical concepts and programming in R?**
Yes, the book integrates statistical concepts with programming in R to address statistical questions and solve real-world problems using data.

**3. Are there practical exercises included in the book?**
Yes, the book features numerous exercises to help readers apply their knowledge and skills to tackle challenging data science projects.

**4. What are the qualifications of the authors of *Modern Data Science with R*?**
The authors are highly experienced professionals in the fields of statistics, mathematics, and computer science with extensive teaching and research backgrounds.

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## Conclusion

*Modern Data Science with R* 1st Edition is a valuable resource for undergraduates seeking to delve into the realm of data science by combining statistical and computational approaches to analyze data and derive meaningful insights. With a focus on practical applications and exercises, this book equips readers with the necessary skills to tackle complex data science projects effectively. The expertise and experience of the authors enrich the content, making it a comprehensive and insightful guide for aspiring data scientists.