PDF Download Learning R: A Step-by-Step Function Guide to Data Analysis
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Learning R: A Step-by-Step Function Guide to Data Analysis
PDF Download Learning R: A Step-by-Step Function Guide to Data Analysis
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About the Author
Richie is a data scientist with a background in chemical health and safety, and has worked extensively on tools to give non-technical users access to statistical models. He is the author of the R packages "assertive" for checking the state of your variables and "sig" to make sure your functions have a sensible API. He runs The Damned Liars statistics consultancy.
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Product details
Paperback: 400 pages
Publisher: O'Reilly Media; 1 edition (September 26, 2013)
Language: English
ISBN-10: 1449357105
ISBN-13: 978-1449357108
Product Dimensions:
7 x 0.8 x 9.2 inches
Shipping Weight: 1.8 pounds (View shipping rates and policies)
Average Customer Review:
4.2 out of 5 stars
19 customer reviews
Amazon Best Sellers Rank:
#101,439 in Books (See Top 100 in Books)
I don’t have a programming background, but I want to learn R, so I use this book as a supplement to an online course. It’s a decent introduction to R, but I will have to buy another book that goes into more detail— I rented “The Book of R†from the library, and I wish I had bought that instead of this O’Reilly book.
If you want to start learning R, there several things you may want to consider. There are two kind of skills you want to cultivate: programming skills and actual data analysis ones. In principle, you can learn techniques alone, but then your creativity as a data analyst will be limited and probably you will end up writing poor code. Alternatively focusing only on coding may make you a good programmer, but it will be hard to get started on putting your skill into practice. Any book should strike a tradeoff in where to stand between training you in these two topics. Cotton's book try its best in this and does a pretty good job. The first part of the book, covering the intricacies of the language is the one I found most useful. I has all sort of good advise and explanations on the data structures and functions you can use. It is appropriately applied - not just about computation and programming, but actually links how they are applied in the actual data analysis. In this sense, this was the most original and interesting part of the book. The second part of the book, covering data analysis techniques was more conventional but still good. As such, there are perhaps better books if you are interested on any of the two sides ("machine learning for hackers" is very good to learn how to apply the techniques and seeing them in action; "Introduction to statistical learning" is a bit more theoretical; Advanced R or The Art of R Computing are unbeatable about teaching the language, although a bit dray).The approach of Cotton is really instructive. He is friendly, he write well in a easygoing fashion and the book is full of useful tips that helped me to understand how the language merge with the technique.The book is not encyclopedic, it does not cover every single topic (there are better books for that, Matloff and Wickhams books are better). Instead, it does a really good job as a tutorial that walks you through many topics that are somehow not covered in many other books -the chapter that covers factors and dates is perhaps not something you will deal with everyday, but very useful if you have to.Overall, I think the book teaches you really well how to play with the R language.A very final remark. I've seen other comments that suggest this is an introductory book. The book hardly takes things from scratch. If you have never written a line of code, you are likely to find it, particularly the first part, pretty dry. It is more an intermediate text, otherwise you will find yourself wondering why you need to know all these pages about data structures if you just want to learn to load a csv file and run a regression.
A gift so no personal opinion. Seems well liked.
Excellent
This book is tremendous. It takes the reader through R without getting bogged down in an explanation of statistics and data modeling. It even includes chapters at the end on writing your own packages.
Very good book.. easy to read and follow.. well worth the price if you'd like to work with R, and I have a few R books already. I really like how he gives his opinion and takes a stand on whether to use some functions over others.. i only wish he didn't spend time talking about the worse way to do it... just give me the best.. which he eventually does.
Well written and easy to follow. I very much appreciated the questions at the end of each segment testing ones ability to practice the material. I would highly recommend this book
A great walk-through of R. Helpful and readable for people who know a bit of programming, and probably for those who don't.
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