Apologies for an awkward title.
I am looking for concrete examples of how it is important to make the distinction "holding all else fixed", when talking about coefficients of predictors in multivariate regression. Examples that would be relatable, for people looking at regression output but not familiar with how regression works.
I want to be able to preempt things when they say "this variable should not be negatively correlated with the response, not positively correlated; the model is worthless!" (exaggerated, of course)