u/ArkarajMukherjee

We were taught basic R in the stat course but many wondered why python wasn't used instead of R. Almost everyone I asked except a few said python supercedes R in "almost" every way.

So my question is, where does R outshine python? Why do most statisticians still use R?

Some pros for R as pointed out by the kind people in comments :

1. R is better for data wrangling and it has piping.
2. It has dedicated packages for many fields which heavily use stats.
3. Data vectorization.

We recently had a first course in statistics, where we covered the usual soup of confidence intervals, MLE, hypothesis testing etc. etc. but the most interesting thing were bootstrapping and Jackknife which just seem to "work". Upon asking the instructor we were told that to fully understand why these work we'd need to devote a whole semester to just these. Coming from a pure math background, stats never sat with me but this has to be one of the most beautiful things I've ever seen in this subject! I really want to try to have a go at it so can you please give me a roadmap to a "proof of why bootstrapping work"? You can assume the standard undergraduate curricula concerning probability theory, analysis, linear algebra etc.