Agreed, but maybe you have to assume that the scientist knows very little about coding for data science, which is effectively what we're talking about here.
I think a major contributing factor to problems like this is people going into the soft/social sciences being more likely to be math/stats AND programming averse. Meanwhile, all sciences continue their long term trend towards applied math via programming. This leads to people using the math/stats via code without understanding very well what it is they are doing, and, naturally, the end result is lots and lots of mistakes.
Or that the material will be taught effectively. Or that the students are contextually prepared to understand the material at that point. Or any of a number of other things that go wrong when people suggest that education is the solution/root to a very hard problem :)
I think a major contributing factor to problems like this is people going into the soft/social sciences being more likely to be math/stats AND programming averse. Meanwhile, all sciences continue their long term trend towards applied math via programming. This leads to people using the math/stats via code without understanding very well what it is they are doing, and, naturally, the end result is lots and lots of mistakes.