Learn R through examples
Aimed for total beginners, this book is written based on the philosophy that people learn faster when they are shown examples and case studies. Instead of explaining the rules, the book largely centers on the analysis of several datasets from the very beginning. So this is an alternative to traditional, more rigorous textbooks on R programming. We start with small and clean datasets and gradually transition into big, messy ones. With each dataset, we hope to tell a story through the analysis. We invite you, our courageous reader, to take on this journey with us. Motivated readers, such as biologists, could easily work their way through this book and learn by themselves. I would encourage you to type in the example code and see the outputs. And then work on the challenges and exercises.
It originally started as materials for 2-hour hands-on workshops intended to give a quick introduction/demonstration for students and researchers who are totally new to R. The workshop has been given many times to different audiences ranging from high-school students to mathematicians. For a 2-hour session, I have to keep it gentle, interactive, and fun, sometimes at the expense of rigor. Instead of explaining all the rules, grammar, and syntax, I found it is easier to focus on one dataset and walk them through some of the analyses possible with R. This material later evolved into as a one-credit online class and then a three credit class. We stick with the unconventional approach of focusing on datasets and examples.
