The Book of R: A First Course in Programming and Statistics

An excellent book. Or rather 3 books in 1 representing: Programming in R, Statistics in R and Graphics in R and therefore excellent value. Unlike some other R books, lots of exercises to practice on. Programming is about practice, practice, practice. I'm an experienced programmer (other languages) and worked through Sections 1 and 2 in about a week of full time work. Obviously I will need a more advanced book at some point but this covered the basics admirably.

Excellent book as an introductory text for learning R - I'm much a newbie and have starting developing in R with more confidence. The sections on matrices is fantastic!

Bought this to help me progress from VBA in excel to some *proper* data skillz. It's a good book. The sections about ellipses could be clearer, but for general principles and guidance, it's been very good. I'm actually still working through the later part of the book, but if you want something to get you up and running, this is a good choice. The first half has (so far) been enough to teach me what I needed. The second half, when I finish it, should be icing on the cake.

Good for getting a strong hold on R

This book is wonderful, It explains everything clearly and has many exercises with solutions. The only drawback is the color of the book. It is in black and white which is very inconvenient when working with plots. When we have 3 plots overlay, different colors would have made a significant difference. I would rather pay more for another book in color. Anyway, it is a very good book.

I almost never write Amazon reviews, but feel compelled to in the case of this gem of a textbook. Quick about me: -solid general computer skills (e.g. Excel), but NO programming background -took statistics in high school, barely passed calculus in college -was inspired to learn R after seeing a colleague use it for data analysis -have been disappointed by R texts that I've encountered thus far, finding them either too advanced or poorly organized/written Why I am giving this book 5 stars: -it is structured very logically, starting with the basics of the language before moving onto programming, statistics, and more advanced concepts -it is accessible to a wide audience, yet goes into the necessary level of detail -it is well written, in an easy, clear voice -an appropriate balance of text vs code examples and graphics -it has effective exercises at logical points to ensure the reader not only understands, but can execute the concepts learned -it is aesthetically very nice -- the spine doesn't crack, the book doesn't warp over time, the font and text size are very readable As a sidenote, I ordered R for Dummies as well. I didn't give it an especially thorough glance, but quickly flipped through it and decided to return it because I knew on first glance that The Book of R was far superior.

I think this is by far the best book to start with R, beginning from the very basics of the code and ending up with how to plot a "sprinkled doughnut" in R. Even though it has about 800 pages in total, it is totally worth going through.

No doubt, the book deserves my five stars. If you’re a Data Science in the making, the first part (programming) might cover more than you ever need while the second part (statistics) is a great start. In other words, if you’re into Data Science with R, this is one of the few must-have books. My personal must have: # 1 - R for Data Science # 2 – Statistical Inference via Data Science (inference based on the tidy concept) # 3 – The Book of R If you’re a Data Scientist in R, you’re really in luck. Unlike using Python, in R there is one book that trumps them all: “R for Data Science”. On the other hand, I feel like all machine learning books in R suck, especially material on classification. Using Python, there are fantastic machine learning books such as “Python Machine Learning” or, of course, “Hands on Machine Learning …”. I fear the subtitle “a first course in programming and statistics” might be misleading. While the book starts more or less at zero knowledge, it covers a lot of ground. As others mentioned, the binding for this thick book is amazing. If you ever considered R vs. Python, I believe “The Book of R” makes your decision easy. Want to do statistics/EDA/visualizations? R is your choice. Want to do Deep Learning? Python is your choice. If you love R, you most likely have a deep appreciation and love for statistics. In this case, you will most likely love “The Book of R.” Without books like “The Book of R” and the people from R-Studio, we all would do Data Science in Python.