Ph.D candidate in sociology Ethan Fosse just switched from Stata to doing 100% of his analysis with R. His reasons?

If you want to do Bayesian analysis or graph modeled coefficients (or work with complex data structures more generally), then R is much easier than Stata due to the object-oriented programming environment. It's unbelievably liberating to be able to save vectors, matrices, data frames, and so on from multiple data sources and manipulations in the same conceptual space. Additionally, R has fantastic graphics capabilities (3-D plots, rotating hyperplanes, social network graphs, and so on), offers excellent tools for analyzing and display so-called big data (for example, check out the "tabplot" command from Google), and is (frankly) a fun, intuitive programming language. If you need additional reasons to be an R convert, keep in mind that R is completely free, open-source, and extensible, with over 5,300 statistical packages (as of April 2012).

Read more about John's conversion at the link below.

Culture Statistics and Society: I'm Converted to R Full-Time

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