Non- parametric hypothesis test

what are degrees of freedom related to?

sample size

what do parametric tests do?

make certain important assumptions about populations from which data are sampled

how do non-parametric tests test differ from parametric tests?

non-parametric tests make fewer assumptions about populations from which data are sampled → can be applied more readily

what is a benefit of parametric testing?

they are more sensitive / powerful than other approaches

common assumptions of parametric testing:

-populations from which samples are drawn should be normally distributed

- variances (standard deviation) if the population that the samples are being drawn from should be approx equal

-no extreme scores in data sets

why are non-parametric tests are less powerful?

because they often throw away actual data → put emphasis on ranks of data instead of actual scores

examples of non-parametric tests:

-mann whitney U

-wilcoxon

-spearman’s Rho

-1 variable t test vs 2 variable t test