"Nonparametric statistics is the area of statistics that deals with data which either does not have a probability distribution or that does not have the distribution's parameters specified. Nonparametric tests are often practically very useful when a data set's distribution is unknown e.g. when testing the correlation between two variables for a regression, it is often inappropriate to assume the variables studied are normally distributed, and therefore a Pearson's correlation is inappropriate and the Spearman rank correlation would be the non-parametric test that could be applied to such data."
"Nonparametric statistics is the area of statistics that deals with data which either does not have a probability distribution or that does not have the distribution's parameters specified. Nonparametric tests are often practically very useful when a data set's distribution is unknown e.g. when testing the correlation between two variables for a regression, it is often inappropriate to assume the variables studied are normally distributed, and therefore a Pearson's correlation is inappropriate and the Spearman rank correlation would be the non-parametric test that could be applied to such data."
"Nonparametric statistics is the area of statistics that deals with data which either does not have a probability distribution or that does not have the distribution's parameters specified. Nonparametric tests are often practically very useful when a data set's distribution is unknown e.g. when testing the correlation between two variables for a regression, it is often inappropriate to assume the variables studied are normally distributed, and therefore a Pearson's correlation is inappropriate and the Spearman rank correlation would be the non-parametric test that could be applied to such data."