I work as a UX Researcher for a mobile gaming company.
We're discussing best practices in analysis, and my colleague suggested that we always use nonparametric tests (e.g., Mann-Whitney U rather than t, Kruskall-Wallace rather than ANOVA) because they do not suffer from the violation of assumptions that parametric tests do.
I've only ever used nonparametrics if I had to (e.g., the data were counts or ranks rather than means). The argument that one should always use nonparametrics doesn't sit well with me, but I certainly haven't done exhaustive research on the subject.
Are there any guidelines as to when we should use parametrics vs nonparametric tests?