This was a half-day workshop on Sunday morning, November 9, ably taught by Jennifer Camacho Catrambone, Ruth M. Rothstein CORE Center, Chicago. Nonparametric statistics are those that are used with ordinal or nominal data, when data are skewed, or when sample sizes are small.
In contrast, parametric statistics are designed to be used with a minimum sample size of 30 subjects per group. Dependent variables are expected to be interval-level; categorical (nominal) dependent variables are excluded (although independent variables are often categorical).
The Chi Square test is an example of a nonparametric test of association between variables. The workshop handout lists numerous others and provides descriptions and assumptions. The class was full of information, but note to self: don’t take statistics classes after spending four days in conference sessions–the brain is tired.