Non-parametric approach to healthcare dataset?
They are not specifically referring to a plot based approach.  They are referring to a class of methods that must be employed when the data is not normal enough or not well-powered enough to use regular statistics.

Parametric and nonparametric are two broad classifications of statistical procedures with loose definitions separating them:


Parametric tests usually assume that the data are approximately normally distributed.
Nonparametric tests do not rely on a normally distributed data assumption.
Using parametric statistics on non-normal data could lead to incorrect results.
If you are not sure that your data is normal enough or that your sample size is big enough (n &lt; 30), use nonparametric procedures rather than parametric procedures.
Nonparametric procedures generally have less power for the same sample
size than the corresponding parametric procedure if the data truly are normal.


Take a look at some examples of parametric and analogous nonparametric tests from Tanya Hoskin's Demystifying Summary:



Here are some summary references:


Another general table with some different information
Nonparametric Statistics
All of Nonparametric Statistics, by Larry Wasserman
R tutorial
Nonparametric Econometrics with Python