In the stats world there is somewhat of a debate going on regarding which statistical analyses programs are “better”. Of course, the answer always depends on what you use it for. Some like the open-source, developing nature of R. While others like the established and tried STATA.
In the world of labor and employment economics and in ligation matters that require data analysis of large sets of data, STATA wins hands down. However, the open source nature of R is appealing in some settings; but the many decades of pre-written (and de bugged) programs make STATA the best choice in most employment and wage and hour cases that require analysis of large data sets. Performing basic tabulations and data manipulations in R requires many lines of code while STATA often has the command built in.
Here are some interesting snippets from the web on the R v STATA debate:
The main drawback of R is the learning curve: you need a few weeks just to be able to import data and create a simple plot, and you will not cease learning basic operations (e.g. for plotting) for many years. You will stumble upon weirdest problems all the time because you have missed the comma or because your data frame collapses to a vector if only one row is selected.
However, once you mastered this, you will have the full arsenal of modern cutting-edge statistical techniques at your disposal, along with in-depth manuals, references, specialized packages, graphical interface, a helpful community — and all at no cost. Also, you will be able to do stunning graphics.