Parametric testing is defined by making one or more assumptions about the population's properties. The most common assumptions to make are that the population will be normally distributed or have data based on an equal-interval scale.
There are two types of statistical tests: parametric and nonparametric. Rarely are nonparametric tests possible or practical, which is why parametric tests are used for almost every type of statistical analysis.
An example of a parametric test is a simple t-test or chi-squared test. A t-test assumes that the data is normally distributed about the mean of the data and is designed to test the validity of a null hypothesis.