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A Beginner's Guide to R (Use R!)
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Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum.
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Product details
Series: Use R!
Paperback: 240 pages
Publisher: Springer; 2009 edition (July 1, 2009)
Language: English
ISBN-10: 0387938362
ISBN-13: 978-0387938363
Product Dimensions:
6.1 x 0.6 x 9.2 inches
Shipping Weight: 14.7 ounces (View shipping rates and policies)
Average Customer Review:
4.1 out of 5 stars
25 customer reviews
Amazon Best Sellers Rank:
#698,455 in Books (See Top 100 in Books)
This is a perfect beginner's guide. There are many other introductory R texts on the market. This one, by far, is the most relatable. The author has clearly taken great efforts in developing a guide for true beginners--rather than assuming one knows programming languages (e.g., Python). The textbook is also accompanied by downloadable data files, whereby you may practice the concepts introduced in this book. I rated this book as 5 stars, because the competition was greatly lacking. Notwithstanding, this book has some room for improvement, however. First, the examples provided in the textbook do not have an answer key. If there was an online answer key, I could not find it. How are readers to know they have reached the correct solution without an answer key? In my opinion, this was a major oversight. Second, I wished the book was a bit longer. I felt like the key concepts were explained very well. However, I wish the text had lengthier examples or even a full project to complete. This would have helped bring the core topics into alignment for me. Overall, the book is relatively inexpensive for a well-written, "ground floor" introduction to R.
I was never able to open this book in my kindle for the PC. It showed up but trying to open it failed every time. The error message said to delete it from my device and re-download. I tried that like 10 times and it always just failed to open and told me to repeat what I had already done over and over again. The kindle support was completely worthless. Can't even return it for a refund like I could a normal order. Guess I will stick to hardback and paperback editions after blowing $40 on this worthless digital book.
This is required for our class and it really is one of those helpful R books in the market. I love the web help that comes with it. I am a total newbie but I was grateful to have this book that I can use as a skill for differential expression analysis of genes. I am hoping though for more information on new R programs that I can use for my dissertation.
If you want to start (from scratch) to learn to use R for data manipulation and graphics get this book. The authors say, in the forward, that it was designed to support a 3 day (8 hour per day) introduction to the R language without teaching statistics and it does a fabulous job. It covers R data types and data manipulation nearly as well as my favorite book on the topic Data Manipulation with R (Use R) but it also does a good job covering basic plots (all the typical one or two variable plots) out to intermediate graphics (making a lattice with lots of pictures) (a good next step for graphics is Data Analysis and Graphics Using R: An Example-based Approach (Cambridge Series in Statistical and Probabilistic Mathematics)) and also gives a very accessible introduction to applying functions to sets of variables and the R version of looping.The organization and flow are excellent. Each chapter has many exercises and as you read their are pointers saying to go try the corresponding problems. There is no answer key for the problems but they are so closely tied to the material that should not be a major issue.The index is okay but not good because there are functions used in the body of the book that are not indexed and it is missing an overall summary index/table that covers all the functions.If the publisher will clean up the indexing, so that it is easier to return and find the information in the book, it is a solid 5 star product. Another possible complaint is that it is very expensive for a 200 page paperback but the quality of the writing offsets for the bloated price.
I've been wanting to learn R for a while now, but teaching and meetings have gotten in the way. I've been using this book for about a month and spend an hour per day. I do the exercises and also type in all of the R code in the book to see what works (though you can download the code from the book's website). I have found the book very straightforward. Certainly R takes some getting used to and ultimately I'll be using it for statistical applications, but, as noted by the authors, this book is written to introduce the reader to R, not to statistics with R. The explanations for what you are doing (and why) are very clear. The authors have experience teaching a well-constructed workshop for learning R, and it shows in the flow of the book. The text is clearly written and the steps are easy to follow. Learning builds from chapter to chapter. I would suggest, however, that though the authors indicate you can skip chapter 4 on simple functions with the first read, enough of what comes later hints at chapter 4 that I found it made more sense to go back and read chapter 4 rather than wonder what was going on. I have not found the same need to read Chapter 6 on the first pass, though I expect it will help in later understanding how to run statistical tests with R.I am an ecologist, and the authors use strictly ecological examples, which also makes the book very accessible. I've also been working on a data set of my own and it is VERY satisfying to take what I've learned in this book and apply it directly to my own data. At my university, we have limited access to major stats packages (Minitab - yes, Systat - no) and the draw to R, a free and very adaptable system, is strong.Aside from R, another aspect of this book that I really like is that the authors use lots of instances of practical "exploratory data analysis" such as examination of data for outliers. These are steps that are easy to forget about and I like the fresh reminder. I'm also intrigued by the authors' hints at what they like and don't like about particular approaches that I've purchased their related book, Analyzing Ecological Data (hasn't arrived yet).In sum - this is a great book for teaching yourself the basics of R.
I bought this as it was recommended to me by a couple of friends. It is well written and easy to follow.
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