26 May 2020 - Many statistical methods start with a statistical assumption that the distribution of measured values can be summarised by relatively few parameters. 

For example, a normal or bell-shaped distribution is completely defined by 2 parameters, the mean and the standard deviation. The commonly used t test that compares the means of 2 groups assumes the data arise from 2 populations and that each has a normal distribution with the same standard deviation but with different means. 

This is called a parametric analysis because the assumed distribution (eg, normal) can be completely summarised by a few parameters (eg, the mean and standard deviation).

Read JAMA Guide to Statistics and Methods