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R in Action: Data Analysis and Graphics with R
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About the Author
Dr. Rob Kabacoff is a seasoned researcher and teacher who specializes in data analysis. He also maintains the popular Quick-R website at statmethods.net.
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Product details
Paperback: 608 pages
Publisher: Manning Publications; Second edition (June 6, 2015)
Language: English
ISBN-10: 9781617291388
ISBN-13: 978-1617291388
ASIN: 1617291382
Product Dimensions:
7.8 x 1.5 x 9.2 inches
Shipping Weight: 2.3 pounds (View shipping rates and policies)
Average Customer Review:
4.8 out of 5 stars
54 customer reviews
Amazon Best Sellers Rank:
#88,164 in Books (See Top 100 in Books)
R in Action does an excellent job showing the power of the R language. The book also serves a way to learn statistics and data science through using the R language.At the beginning the examples are practical, showing how to make graphs based off data sets that come packaged with R. Sometimes packages are required to install to get the examples running, and the author is clear about how to do this.In chapter eight there was an excellent description about Regression analysis. I knew what regressions were, but this explanation helped clear up some confusion I had. The author says (p.167): "It's [regression analysis] a broad term for a set of methodologies used to predict a response variable (also called a dependent, criterion, or outcome variable) from one or more predictor variables (also called independent or explanatory variables).Following this explanation is a concrete example given showing how to predict the number of calories a person burns on a treadmill based off different factors. I liked that the author defined all the terms, and then gave a concrete example. It is a pattern throughout the book that worked very well.The later parts of the book briefly dive in machine learning and more advanced data science concepts.The main focus of the book is on statistics, graphing, and plotting. This worked well, because it shows the areas where R shines compared with other languages. Luckily for the reader the author knows which techniques work well, and states when certain data analysis techniques work better than others. The author remains humble throughout, stating when he finds a topic complex.R in Action is a great resource for learning R and learning statistics. Explanations transition from easy to hard in a logical manner and this book will be useful for data scientists of all experience levels.
I have read quite a few books on R, and will rate this as perhaps one of the best if not the best. The author has explained the material with excellent clarity, the examples are relevant to real-world applications, and the code executes well using either base installation of R (with added packages) or R studio. Also, the author has managed to concurrently develop both data analysis and data visualization (graphing), which helps the reader, and exposes the capabilities of R very well. The range of topics covered in this book is very broad and gives a good overview of the field. As a clinician with interest in epidemiology, I found almost everything needed for beginner or intermediate level applications. Also, if one works through this book diligently, s/he will be in a very good position to follow more advanced topics (like multilevel models) from other resources.I have only one issue with the book (which is a generic issue with most statistics or data science books centered around a software). That is, it contains very little, if any, mathematical basis or details of the methods being discussed. These days, statistics is taught "thorough" a software. Hence, it is artificial to separate mathematical statistics from computational aspects. I am waiting for a book which will start with the mathematical aspects including derivations of the theorems/equations, give examples of real world applications, and illustrate the application in R.One minor issue is related to very poor quality of the binding of the book. In the copy that I received, perhaps the pasting was defective, and as soon as I first opened it, the first page tore off. Soon, the binding opened up and pages/sections started falling off. I am not sure if this is just limited to the copy that I got or is a systemic issue.
Overall quite a fan and recommend the book! I am a graduate student who was struggling with some analyses, and this provided a great overview on the code + logic behind the analyses in a way that helped me get what I needed to do done quickly (quicker than looking up internet sources). Seems like it's going to be a great reference to have on hand at all times when putting R into practice with research. The one thing (thus far) I am disappointed with is that the code for graphs isn't complete -- frequently will say that the following code produces graph #xyz. However, the code really only produces the most basic version of the graph in the book, and they don't include the extra code for ACTUALLY reproducing (which would be handy if new to graphs and trying to figure out some basic formatting manipulations without a lot of work)
Excellent book . If you are new to Data Analysis it will more than meet your needs. The first few chapters copy basic R , input , output , data types. If you already know R , you will find that a quick review will show you ways to upload most any type of data including Excel spreadsheets.Chapters 7 on actually cover college level statistics including one-way and two-way tables, t-tests, regression . For statistical reference and data modeling the graphics that are included use the latest library's so you won't be wasting time trying to write your own functions. Chapters 12 on are pretty advanced statistics with real world examples.
I am a graduate with master degree in a top-ranked university in US. I bought this book because I wanted to change my career. My background is I had two graduate-level statistical classes in my program. However, after review this book, I find the content is much better than my courses. I paid more than 10 thousand dollars to the two courses!!!!Don't waste you money for the degree! This book is much better than these courses.
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