Promoting ease of use of tools and simplification of harder problems is great, but this is a really, really dangerous thing to make easy and oversimplified.
Nope nope nope nope nope.
Promoting ease of use of tools and simplification of harder problems is great, but this is a really, really dangerous thing to make easy and oversimplified.
Nope nope nope nope nope.
SPSS has, shall we say, a less than savory reputation.
All this to say that there is a market for something much friendlier than R. R is used by pure statisticians, data scientists and the like, but most social scientists prefer Stata, which has pretty legit statistical routines as well as a point-and-click UI.
R is objectively a bad programming language. However, it is by no means inaccessible. I have no statistics background whatsoever, and I managed to learn enough R to be dangerous in a mere week. Other than the 1-based indexing and the utterly disgusting dynamic dispatch mechanism (you could simply not to use the latter), R is surprisingly pleasant to use. What I enjoyed the most is that vectors and matrices are first-class values, not objects that are referred to through pointers. It's probably copy-on-write under the hood, but I don't need to care. Hallelujah!
I think it surprisingly makes a lot of sense to social scientists, in spite of seeming backwards to computer scientists. I remember being in school and using STATA, and just plugging in numbers to get through exercises too quickly to bother understanding what the labs were about.
R seems to make you stop to realize what you are doing at the right moments, then uses a lot of magic to abstract away almost everything else.