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Statistical Analysis with R
If you are a data analyst, business or IT professional, student, educator, researcher, or anyone else who wants to analyze data effectively this practical, step-by-step guide packed with clear examples, screenshots, and code will help you quickly become proficient in data analysis using R. Prior experience of R is not needed; knowledge of other programming languages, software packages, or statistics may help but is not needed. After downloading and installing R, you learn its fundamentals with a basic R program then learn to import external data for analysis, manipulate data using variables, and store and edit data in an R workspace. Next you learn to use various statistics for global understanding of your data then create predictive models using regression analysis and customized functions to assess the implications of your predictions. Finally you learn to organize analyzed data to convey your predictions to others effectively and map your statistical analysis with charts and graphs.
286 pages, Paperback
First published January 1, 2010
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Displaying 1 - 2 of 2 reviews
January 19, 2011
The programming language R is a standard for statisticians. And it is free software which runs on Windows, Mac and Linux.
You can learn much online about R, but if you prefer a bona fide book, there are also many to choose from. I just finished one of those: Statistical Analysis with R by John M. Quick.
The book is colorful and ludic which is a good idea for a “Beginner’s Guide”. The layout is attractive, there are many detailed examples. I like the pedagogy: the author wants you to learn by doing. However, the book is poor as a reference: the coverage is limited despite the 300 pages and the chapter summaries are strictly non-technical.
Overall this is a good book for people with no programming background who just want to use R to load data, do ANOVA tests and simple models. They will find step-by-step instructions down to the installation of the software, complete with screenshots of every step. This could be a good book for scientists or business people who want to try R as a substitute for Excel.
Disclaimer: I got a free copy of the e-book from the publisher with the expectation that I would publish a review.
You can learn much online about R, but if you prefer a bona fide book, there are also many to choose from. I just finished one of those: Statistical Analysis with R by John M. Quick.
The book is colorful and ludic which is a good idea for a “Beginner’s Guide”. The layout is attractive, there are many detailed examples. I like the pedagogy: the author wants you to learn by doing. However, the book is poor as a reference: the coverage is limited despite the 300 pages and the chapter summaries are strictly non-technical.
Overall this is a good book for people with no programming background who just want to use R to load data, do ANOVA tests and simple models. They will find step-by-step instructions down to the installation of the software, complete with screenshots of every step. This could be a good book for scientists or business people who want to try R as a substitute for Excel.
Disclaimer: I got a free copy of the e-book from the publisher with the expectation that I would publish a review.
August 12, 2023
It was really strange for me finishing this book, I had it open a thousand times and closed another thousand.
The story serving as a leit-motiv pushed me in, the long variable names and the amount of space that didn't added much to learning pushed me back out.
Today, almost 8! years after first opening it I can say I went throught it finally.
It's not a bad book, and it's probably quite good for newbies and people who had never opened R. Although going through it without using RStudio is something I would probably not recommend.
The story serving as a leit-motiv pushed me in, the long variable names and the amount of space that didn't added much to learning pushed me back out.
Today, almost 8! years after first opening it I can say I went throught it finally.
It's not a bad book, and it's probably quite good for newbies and people who had never opened R. Although going through it without using RStudio is something I would probably not recommend.
Displaying 1 - 2 of 2 reviews