Starting with data types, syntax, and control structures, the book gently introduces statistical concepts such as exploratory data analysis, probability, hypothesis testing, and regression modeling — all illustrated through real-world datasets and hands-on R examples.
You’ll learn how to:
- Write clean and efficient R code using functions, loops, and conditionals
- Work with vectors, data frames, lists, and external data
- Use R for statistical summaries, tests, and simulations
- Visualize data with base R,
ggplot2,ggvis, andrgl - Interpret and communicate your analysis through professional-quality graphics
Each chapter features:
- Practical exercises with solutions
- Diagrams and step-by-step breakdowns
- Real-world use cases across disciplines
With over 75 pages of structured content, Learning R will not only teach you how to program in R, but also help you think statistically. It’s an essential resource for anyone entering the world of data analysis.
Reviews
There are no reviews yet.