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Edgar J. Treischl
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Practice R - Summary
"Practice R" is an invaluable resource for social science students and anyone interested in mastering the R programming language. This interactive textbook introduces R in a non-technical and pragmatic way, making it accessible even for beginners. The book covers all the essential steps of applied empirical research, from data preparation and analysis to visualization. It also provides guidance on data collection, report generation, and automating error-prone tasks. Accompanied by an R package, "Practice R" offers interactive tutorials and source code for each chapter, allowing readers to practice and apply their knowledge immediately.
Key Ideas
Comprehensive Introduction to R
"Practice R" offers a thorough introduction to the R programming language, tailored specifically for social science students. It breaks down complex concepts into manageable steps, ensuring that readers can follow along and build their skills progressively. This makes it an excellent starting point for anyone new to R.
Practical Application of Empirical Research
The book emphasizes practical application, guiding readers through the typical steps of applied empirical research. From data preparation and analysis to visualization, "Practice R" covers it all. This hands-on approach ensures that readers can immediately apply what they learn to real-world research projects.
Interactive Learning with R Package
Accompanying the book is an R package that includes interactive tutorials, source code for each chapter, and templates for report generation. This additional resource enhances the learning experience by providing practical exercises and challenges that reinforce the concepts covered in the book. It also allows readers to practice and refine their skills in a supportive environment.
FAQ's
"Practice R" is primarily aimed at social science students and anyone interested in learning the R programming language, especially beginners who want a non-technical and pragmatic introduction.
"Practice R" covers essential steps of applied empirical research, including data preparation, analysis, and visualization. It also provides guidance on data collection, report generation, and automating error-prone tasks.
The R package that comes with "Practice R" includes interactive tutorials, source code for each chapter, and templates for report generation. These resources offer practical exercises and challenges that help reinforce the concepts covered in the book.
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