Main question up front: what are differences between econometrics/social science statistics that and industrial statistics that people switching between the two should be are of?
I got a PhD in mathematical statistics in December and have a job now that is in a different area of statistics than I studied and cared about for years. I studied econometrics for years but now I work in operations research and use industrial statistics. In particular, most of the studies I see now involve designed experiments; this is almost never the case in econometrics.
As my job is to be a consultant, I feel bad whenever I make wrong claims or bad advice to people who are not experts in what I know, and I think I've now twice made a wrong statement. Regarding whether to drop terms from statistical models with insignificant p-values or whether one should favor including or excluding terms that border on being relevant, I tapped on my econometrics lessons and said: the cost of including an irrelevant term is larger standard errors but the cost of excluding relevant terms is biased parameter estimates, which is worse. This is technically true, but biased parameters are irrelevant in the context of designed experiments. In order for parameters to be biased, regressors need to be correlated with each other; since they cannot be correlated in a designed experiment, omitted variable bias cannot be a problem, or should not be expected to be a problem.
(Aside: I still tend to favor including potentially irrelevant factors, though, and deleting parameters from models based on large p-values or selecting parameters based on aggressive AIC optimization makes me very nervous; I would rather adopt a procedure that accounts for model selection automatically, such as LASSO regression, or use some other basis for deleting parameters other than p-values, such as looking at AIC for hand-selected models or looking at Normal plots, but model selection is still what keeps me up at night.)
This is the second time in the span of a few months I offered incorrect advice (the other time hinged on a misunderstanding of terms) and I want to do what I can to minimize this occurrence. My background in econometrics has revealed itself to be a potential stumbling block (sometimes; other times it can be an advantage) and I would like to see a list of other potential major differences between econometrics or social science statistics and industrial statistics that I should be aware of. What else is something I shouldn't say is true because it's a concern in econometrics since it's not a concern in industrial statistics?