Fair, but even though their precise knowledge is inaccurate they do have a correct understanding that the quant skill requirements in psych are << those in physics, maths.
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Adding in coding changes nothing. In fact it helps relieve rote learning SPSS menus.
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Agreed... now I have 2 concrete concerns: 1. Where will the time come from to teach coding? (Not sure that "From the time not spent learning SPSS clicking" will be sufficient.) It's easy to have ideas for adding to a curriculum, but nobody wants their stuff to have less time.
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ex1 <- read.csv("ex1.csv", header = T) plot(ex1$iv, ex2$dv) lm(dv ~ iv, data = ex1) Is the learning curve at that level really do high? (Genuine Q - I use it every day so can't judge!)
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Yes, there's a lot to unpack there. You first need to teach them what a variable is. You also need to teach them what a function is, and that code executes in order. I think a lot of people forget how hard it is to code if you have literally never done it before.
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In the 1980s I taught a course for engineers using our CAD product which had a powerful programming language built into it. They understood sin(x) no problem, but the idea of writing your own fn(x, y, z) that returned a number was often really hard for them to understand.
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Other issues: - Local variable scope (different in every language!) - Strings versus character vectors versus names - Vectors versus lists Many of these things require a "mathematical/logical" mind, which may be partly orthogonal to talent for statistics.
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Example of the scope problem. > f<-function() {print(X); X<-X+1; print(X)} > f() Error in print(X) : object 'X' not found > X<-3 > f() [1] 3 [1] 4 > print(X) [1] 3 Now replace X<-X+1 with X<<-X+1. Think how much understanding you need to master this.
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I've programmed in ~25 languages, ~15 of those for pay, and I found some R stuff a bit tricky at first. For example, imagining how the parser must work for constructs like formulas to be possible (as opposed to as.formula(string)) is a little mind-bending.
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I used to incline towards pessimism, in that people who are put off by "(the idea of doing)" stats may also not like "(ditto) coding", but if those are correlated .9 then maybe there's no extra penalty for adding coding.