When it comes to statistical analysis software, SPSS and R are the most common you'll hear about in psychology. My understanding is that SPSS is still taught to most undergrads, as was the case when I was in undergrad. There past decade has seen movement toward using R, which provides an easier basis for reproducibility.
To use SPSS, you need to click some menu options.
To use R, you have to learn basic programming: variables, data-structures, if-then, loops.
Teaching R is getting more popular, but it isn't the norm for undergraduate students yet.
The most succinct reasons appear to be pragmatic:
- most undergraduates studying psychology are not comfortable enough with programming to learn R.
- most graduate student teaching assistants don't know R well enough to support a class.
- most psychology professors don't know R well enough to teach it.
Don't get me wrong: I think R is the way to go if you have a choice of which you learn.
I think that using R is undeniably superior, but teaching R is undeniably more challenging.
Pragmatically speaking, most psychology undergraduates are not prepared to learn R.
That is, they don't have any background in programming; that isn't part of the requirements for enrollment in psychology. In fact, most graduate students in psychology are also not prepared to learn R! Many struggle to learn R and many fail to learn proper programming technique. Unfortunately, graduate students in psychology tend to lack the foundations taught to computer science students that would help them pick up R more easily.
Psychology graduate students that fully understands programming standards, algorithms, data-structures, and data-management are rare.
Psychology undergraduate students that understand the same are even more rare.
If you want to stand out, developing skills in R could help.
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