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February 7, 2019

After attending months of Twitter discussion about what could be the best software–R or Python–for data science several months ago, this is now the time of the R vs. Stata debate, here and there. Arguably, Stata is a paid software and does not offer the same scripting facilities than R for some tasks, mainly non-statistical tasks. However, what's the point? Did anyone ever mentioned the fact that Stata has a GUI which completely mimics the command-line operations, so that people afraid of typing commands or just interested in running a logistic regression on a well-formed dataset can just do it in under a minute? It is slow with some estimators or optimization approaches (e.g., gglamm), and we had to wait a bit long to get full support for unicode and XLS, better graphical rendering, etc. But the versioning system allows to repoduce any result prior to the current version of Stata. And it does interact very well with Stan and R, too. The question is not which software is better, the real question is who's the end user? #rstats #stata