Parametric tests are suitable for normally distributed data. Nonparametric tests are suitable for any continuous data, based on ranks of the data values. Because of this, nonparametric tests are independent of the scale and the distribution of the data.

Is parametric the same as normal distribution?

Parametric tests assume a normal distribution of values, or a “bell-shaped curve.” For example, height is roughly a normal distribution in that if you were to graph height from a group of people, one would see a typical bell-shaped curve. This distribution is also called a Gaussian distribution.

Is normal distribution parametric or non-parametric?

Parametric tests involve specific probability distributions (e.g., the normal distribution) and the tests involve estimation of the key parameters of that distribution (e.g., the mean or difference in means) from the sample data.