Question

What are the assumptions and advantages of nonparametric methods?

Answer 1

What are nonparametric methods?

The parametric tests require various assumptions which reduce their applicability while the nonparametric methods do not depend upon the population parameters such as mean and variance and hence, that's why they are called nonparametric methods.

The assumptions of nonparametric methods are below:

(i) Sample observations are independent.

(ii) The variable under study is continuous and so has a continuous distribution.

(iii) Lower order moments of the distribution exists.

The advantages of nonparametric methods are below:

(i) No assumption about the population distribution is required except that distribution is continuous.

(ii) The statistical hypothesis does not depend on population parameters and so named as non-parametric methods.

(iii) Non-parametric methods are easy to understand, easy to apply and do not require complicated sampling theory.

(iv) Non-parametric techniques can be very efficiently applied when the data is measured in Nominal scale.

(v) The sign test is the simplest of the non-parametric techniques and is often used as a non-parametric alternative to one-sample t-test.