I am a graduate student in statistics and as such involved in a couple of collaborations with applied scientists (economists, foresters, …). These collaborations are fun (most of the time) and I do learn a lot, but there are also some complications, for example:
- Sometimes my view of what a good statistical model is differs from the background of my collaborators and the common practices in their field. It is then difficult to convince them of trying out something new, either because they struggle to understand the model or because they are reluctant to change their habits
- When proposing to use different statistical methods, I often have the impression that my collaborators consider this a criticism of their “standard” methods. However, it is by no means my intention to criticize anybody for their statistical knowledge or habits
- And finally there is the other extreme: Some people expect too much. They think that I can miraculously extract interesting information from their data without their assistance. Of course, this is not true, especially if I miss the subject-specific background
I could probably think of more points but these are the first that came to my mind.
The questions I am asking you are:
- Do you experience the same or similar difficulties in your collaborations? How do you confront them? Generally, what do you do to be a good statistical collaborator?
- Are there any third-party resources on this topic, i.e., the soft skills needed in collaborations between statisticians and applied scientists?
Note: This question is more or less the converse of this one.