If you are looking to delve into the world of exploratory data analysis (EDA) using R, “Exploratory Data Analysis Using R” is a valuable resource. Authored by Ronald K. Pearson, a Senior Data Scientist with extensive experience in data analysis and software development, this book serves as a classroom-tested introduction to EDA techniques using R.
The book covers a wide range of topics essential for understanding EDA, including the exploration of different aspects of data – good, bad, and ugly, the mechanics of using R for data analysis, working with external data, linear regression models, crafting data stories, creating R functions, text data analysis, predictive modeling, and more. Whether you are an advanced undergraduate student, entry-level graduate student, or a professional with little prior exposure to data analysis and programming, this book offers a non-mathematical approach to mastering EDA concepts.
Ronald K. Pearson’s background in Electrical Engineering and Computer Science, coupled with his practical experience in various software domains, adds depth to the content of the book. The inclusion of exercises at the end of chapters enhances the learning experience, making it suitable for classroom use. Additionally, an instructor’s answer manual is available to aid in teaching and learning.
About the Author:
Ronald K. Pearson’s expertise extends beyond this book, with a range of publications and contributions to the field of data science and software development. His academic background, coupled with industry experience, enriches the content and practical relevance of “Exploratory Data Analysis Using R.”
FAQs
1. Who is the author of “Exploratory Data Analysis Using R”?
The author of the book is Ronald K. Pearson, a Senior Data Scientist with GeoVera.
2. What topics are covered in the book?
The book covers data exploration, working with external data, linear regression models, crafting data stories, creating R functions, text data analysis, predictive modeling, and more.
3. Is the book suitable for beginners?
Yes, the book is designed for both advanced undergraduate students, entry-level graduate students, and professionals with little prior exposure to data analysis and programming.
Conclusion
“Exploratory Data Analysis Using R” is a comprehensive guide for individuals looking to enhance their understanding of EDA techniques using R. With a practical approach, clear explanations, and exercises for reinforcement, this book caters to a diverse audience ranging from students to professionals entering the field of data analysis.
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