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 wassem wrote: Hi Tom I liked your article, you covered all the benefits of the thin client computing. In the article you mentioned the low power benefit, and mentioned the HP computer, as low cost solution, but I think that our product the Cubox that Costs 120$ and needs only 3 Watt of power could be another excellent solution.
May. 27, 2013 08:08 AM EDT
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