Parametric statistics are based on assumptions about the distribution of population from which the sample was taken (e.g. t-test).
Nonparametric statistics are not based on assumptions, that is, the data can be collected from a sample that does not follow a specific distribution (e.g. Mann-Whitney-Wilcoxon test).
