> For my use case, R is absolutely terrible compared to some for profit statistical package / language.
Which one? I've switched most of my work over to Julia, but I'd much rather use R or Python than Stata or SPSS.
Which one? I've switched most of my work over to Julia, but I'd much rather use R or Python than Stata or SPSS.
Academic research, so more econometrics/data science work, but I have some experience with application programming that I've managed to leverage.
> Most people I know who are either statisticians or scientists first and programmers only reluctantly love Stata and SPSS
They are good to the extent that a lot of published - social science - research uses terms and methods that assume you're using one of the two. Of course, having an ok point and click interface also helps.
However, data access, aggregation, and cleaning are easily ninety percent of what's involved in even basic econometric(y) research. It is orders of magnitude easier to do all of this programmatically in R. Once you start working with larger datasets, or once performance becomes an issue, you pretty much have to transition to Python, Julia, or something similar by default.
Teaching them to do statistical analysis in Julia will involve you spending 80% of your time teaching them Julia and maybe 20% of your time teaching them statistical analysis.
This works until they run into a use case that doesn't involve running various forms of regression analysis on panel data.
In the parent comment's case, I could imagine that there's an expectation that someone doing neuroscience research will eventually have to expand beyond what's possible in SPSS. In this case, it may make sense to go through the effort of teaching them how to program in Python or Julia.
I find using Python and/or R to be very helpful for teaching, since you can implement the stats procedures using primitives (prob. calculations), so you get some experience with how things work.
Sure it requires some "coding" but nothing harder than using a calculator, so I think it's worth learning.
Julia is a bit more involved (need to learn something about data types), but still would be manageable.
From time to time, I still have to use SPSS. Again and again I'm flabberghasted how bad this overpriced piece of software is.