In the previous units, the methods used were based on making some sort of underlying assumptions about the data − for example, “the data are normally distributed”. However, there are situations where the assumptions about the data do not hold, and the non-parametric statistics approach may be an alternative. In this unit, we will discuss the different non-parametric methods for testing hypotheses where assumptions are not made about the probability distribution of the variables under consideration.
