A test in which conditions, i.e. parameters, are assumed about the population from which the data is taken
On the other hand, a non-parametric test does not set parameters, i.e. defining qualities, about the population from which data was gained.
The assumptions a researcher makes for this test to be valid
Normality: Data have a normal distribution (or at least is symmetric)
Homogeneity of variances: Data from multiple groups have the same variance
Linearity: Data have a linear relationship
Independence: Data are independent
