I'm frequently on the "data analysis" end of this spectrum when I work together with biological psychologists (or psychological biologists). Basically, I run the analyses, do all kinds of diagnostic checks, plot enlightening plots and discuss all this with the biologists and the psychologists. They in turn look at my plots and know what results make biological/psychological sense, e.g., which biomarkers are frequently associated with what disease or other, or what the recent literature has to say about some specific relationship. Or, much more basic, the biologist can tell me which measurement makes sense, and which one has to be a measurement error.

This is the relationship between data analysis and data interpretation.

I think that this kind of division of labor makes a lot of sense. Statisticians simply know a lot more about statistics than do psychologists, doctors or biologists. And (sorry) I have seen very disheartening things happen if subject matter experts think they know enough statistics to run complicated analyses themselves. Yes, some psychologists do have an excellent grasp of statistics - but most simply don't. And that's how it should be. After all, I don't expect my car mechanic to be able to repair my refrigerator, either. (It should go without saying that I don't think statisticians shouldn't arrogate any specific subject matter expertise to themselves, either.)

The relationship between subject matter expertise and statistical knowledge is a frequently discussed topic in what is nowadays called Data Science. I have expounded on my point of view here.

I'm frequently on the "data analysis" end of this spectrum when I work together with biological psychologists (or psychological biologists). Basically, I run the analyses, do all kinds of diagnostic checks, plot enlightening plots and discuss all this with the biologists and the psychologists. They in turn look at my plots and know what results make biological/psychological sense, e.g., which biomarkers are frequently associated with what disease or other, or what the recent literature has to say about some specific relationship. Or, much more basic, the biologist can tell me which measurement makes sense, and which one has to be a measurement error.

This is the relationship between data analysis and data interpretation.

I think that this kind of division of labor makes a lot of sense. Statisticians simply know a lot more about statistics than do psychologists, doctors or biologists. And (sorry) I have seen very disheartening things happen if subject matter experts think they know enough statistics to run complicated analyses themselves. Yes, some psychologists do have an excellent grasp of statistics - but most simply don't. And that's how it should be. After all, I don't expect my car mechanic to be able to repair my refrigerator, either. (It should go without saying that I don't think statisticians shouldn't arrogate any specific subject matter expertise to themselves, either.)

The relationship between subject matter expertise and statistical knowledge is a frequently discussed topic in what is nowadays called Data Science. I have expounded on my point of view here.