"Parametric" versus "Non-Parametric": categories of tests that either require "Normal" or "not Normal" data. Parametric tests are preferred to non-parametric.

Common tests: T-test (paired), Mann-Whitney U, ANOVA, Anderson-Darling, etc.

Other terms include "significant". This is a measure of if the data indicates your hypothesis to be valid or not. When you test your hypothesis to a certain degree of likelihood (normally 95%), a "p-value" of less than 0.05 would indicate that you would reject your "null hypothesis" (i.e. data sets are not different) and accept your "alternative hypothesis" (i.e. data sets are different).