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

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/writtenWhy 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 readableAs 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.

Great book! Very helpful in learning R! Would recommend to others due to its coding examples. It also has a unique approach for learners.

LoveThis book! It’s on my nightstand mom

This wasn't the book for my needs, but it is still an excellent book on R. I'm not a super user of statistical software and I was hoping to use R for checking for normalized data and maybe running a standard deviation. And since tableau can pass scripts through to R, I thought it was time to learn it. I was hoping for a quick "go-to" book to look up just the information I needed, but this is a full, step by step course to learning everything about R.It is well written and has a great combination of learning and practice sessions. If I was inclined to teach myself everything about R, this would be the way to go. The author has a fun way of explaining statistics and program language that makes it a bit more fun to read and he brings some creative names into examples. I didn't realize it was such a hefty book, it's the size of a full text book.So even though this wasn't exactly what I was looking for, it will likely be exactly what 90% of readers are looking for. If you want to learn all the ins and outs of R, this is the book to purchase.

I come back to this book monthly. This book makes learning programming in R fun. The book also made me more comfortable with Statistics and Probability (Part 3) as well as Statistical Testing and Modeling (Part 4). I know I will be a much better Computational Statistician and Quantitative Analyst because of this book.

I've got a very good stats background from grad school and a long tech industry career in research. I've used SPSS for decades and made heavy use of SPSS syntax, so I delayed moving to R because I could do so much in SPSS so easily. But with some down time and having never gotten over the hump with online tutorials--including datacamp--I bought this book to work through R skills ground up.What a great decision. I can't recommend this book highly enough.I was transfixed with working through each example in the text and each practical exercise at the section breaks despite it being 400+ pages before I encountered a statistical concept/explanation I wasn't already very familiar with. I was re-learning, re-thinking, refreshing the way I go about working with data. And I was wishing I had done this a long time ago.Take your time, do it right, learn as you go, take notes for yourself on the side, save code snippets for future-you to leverage in your work, and enjoy the learning. I worked through this as I would a textbook despite being long out of school. I suppose it might make a good reference without doing that, but it will be a much better reference/reminder for me now that I have thoroughly internalized the way of working with R it provided me.

For everyone who wants to start a Data Science career this is a great source.

This isn't a bad book, just not what I was looking for. I was looking for a book that easily walked me thru the syntax and process of R programming as a R novice. This seemed to be, for me, not so much a primer on data importation, cleaning up and transforming your data or production of quick & visually compelling gplot2 graphs and table making, rather it was more of a this is how to program for regression and statistical testing. It was tedious for me to extract the specific information I wanted and needed. I wanted to know the time, and this book told me how to build a clock.