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

I’ve used both R and Stata for a long time, but these days I use Stata much more frequently than R. While R is useful for some kinds of graphics (especially three-dimensional graphics) and some statistical procedures (for example, finite mixture models), in general I prefer Stata as the go-to statistical program. The reasons are clear: Stata has superior help files for almost all ado files, Stata graphics are excellent (even contour plots are available in Stata), cleaning data is a breeze in Stata but awkward in R, labeling data is much efficient in Stata (in fact, as far as I can tell R does not allow for labeling variable names, while Stata allows for labeling levels of a variable, the variable itself, and the data set), and for many procedures Stata’s syntax is much more parsimonious than R’s.

Yet, R is worth learning because the 3-D graphics available are often extremely useful for exploring the data, and there will certainly be cases in which R will have statistical procedures that are unavailable or cumbersome in Stata (Bayesian analyses and finite mixture models come to mind, for example).

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**Culture, Statistics, and Society**.

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