In: Math
agree or not?
What is a nonparametric test? What is a parametric analysis?
Parametric tests assume underlying statistical distributions in the data. Therefore, several conditions of validity must be met so that the result of a parametric analysis is reliable. The student’s t-test for two independent samples is safe only if each sample follows a normal distribution and if sample variances are homogeneous. Nonparametric tests do not rely on any delivery. They can thus be applied even if parametric conditions of validity are not met. Parametric tests often have nonparametric equivalents. You will find different parametric tests with their equivalents when they exist in this grid. 3.
what is the difference between a nonparametric test and a distribution-free test?
While nonparametric tests don’t assume that your data follow a normal distribution, they do have other assumptions that can be hard to meet. For nonparametric tests that compare groups, a common assumption is that the data for all groups must have the same spread dispersion. If your groups have a different spread, the nonparametric tests might not provide valid results. On the other hand, if you use the 2-sample t-test or One-Way ANOVA, you can simply go to the Options sub dialog and uncheck Assume equal variances. Voilà, you’re good to go even when the groups have different spreads.