R is the only real game in town for free software for scientific computing these days.<p>From a political perspective R was in the right place at the right time. It was a decent high level language that could handle matrix processing gracefully. Scipy&#x2F;Numpy  weren&#x27;t ready for production yet. The others were Matlab, SAS, and Stata, all of which R makes look like APL.<p>I&#x27;m glad the field has a more healthy open source landscape with worthy competitors in the form of Julia and Numpy&#x2F;Scipy.<p>R&#x27;s biggest sin is failure to force people to use functional paradigms by providing juuuust enough imperative sugar to make average Joe programmer feel at home. <i>R is a functional language,</i> and that&#x27;s the principle under which is should be taught.<p>That said, R also has a large number of main technical strengths:<p>1. Fast basic statistics within the REPL so you can test hunches quickly.<p>2. Cutting edge algorithms that often aren&#x27;t implemented anywhere else.<p>3. Hugely strong engineering packages for civil, environmental, defense, aerospace and basically any IRL engineering field you can think of.<p>R comes free, with these advantages and many more for the average lab tech.