Graphical Data Analysis with R

Graphical Data Analysis with R: that’s the title of Antony Unwin’s new book.

Here are the chapter titles:

Ch01 Setting the Scene
Ch03 Examining continuous variables
Ch04 Displaying Categorial Data
Ch05 Looking for Structure
Ch06 Investigating Multivariate Continuous Data
Ch07 Studying Multivariate Categorical Data
Ch08 Getting an Overview
Ch09 Graphics and Data Quality
Ch10 Comparisons
Ch11 Graphics for time series
Ch12 Ensemble Graphics and Case Studies
Ch13 Some Notes on Graphics with R

If you click on the link above you’ll see the images and code for all the graphs in the book. So you can decide if it’s for you.

Personally, I’d start with time series and scatterplots rather than histograms—I’m sort of down on the idea of 1-d distributions being the first thing people learn in statistics—but I think that for teaching, what’s most important is not exactly what topics are covered or in what order, but that the course as a whole is clearly and sensibly organized. And for that, this book could definitely do the job. Compared to most books on R, which tend to sprawl in all directions, Unwin’s book is focused, students have a clearly defined set of skills to learn, and these skills are framed statistically (for example, “Studying multivariate categorical data,” not “Making a mosaic plot”). Actually I don’t really like mosaic plots and, unlike Bruno Frey, I’d be happy never again to see the Titanic data in any publication, but that’s irrelevant. It’s not about me here, it’s about students getting started on graphical data analysis. Maybe the second edition can have a chapter on our new favorite example.

P.S. I just noticed—there’s no chapter 2! Whassup with that?

2 thoughts on “Graphical Data Analysis with R

  1. I agree with scatter plots. I actually started this semester (first class) with looking at gap minder and then for our first R plots we did scatter plots of state level data. They are very rich and actually students understand them pretty well.

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