**Culture, Statistics, and Society**, and kindly contributed to R-bloggers)

Stata has a large number of graphics capabilities (and I highly recommend Stata over other statistical packages for a variety of reasons), but in a few instances R is more useful. In particular, I find R useful for creating beautiful scatter plot matrices and 3-D graphical displays. To my knowledge, currently these kinds of graphics are very difficult (if not impossible) to create in Stata 12. What I like about scatter plot matrices is that can have a high data-to-ink ratio, packing together fitted lines, scattered data, histograms, correlations (proportional to the size of the correlation), and statistical significance “stars” (since reviewers seem to like them). Moreover, I like that all the information effectively puts the “stars” associated with statistical significance in appropriate context: there is an incredible amount of variability in the size of correlations and distribution of data among all the “three-star” correlations, underscoring the limited usefulness of statistical significance as a tool for understanding the social reality given to us by data.

**leave a comment**for the author, please follow the link and comment on his blog:

**Culture, Statistics, and Society**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...