What are parametric and non-parametric test? Write some advantage and disadvantage of non-parametric test.

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Suresh Chand · Accepted Answer

Parametric statistics are based on assumptions about the distribution of population from which the sample was taken. It is used in testing of hypothesis and estimation of parameter.  Non-parametric statistics are not based on assumptions, that is, the data can be collected from a sample that does not follow a specific distribution. It is also used in testing of hypothesis and but not in estimation of parameter. The advantage and Disadvantage of Non-parametric Test are: Advantage: It is easier to explain and understand. In many of these tests, the computational burden is relatively lighter. So they remain quick and easy to apply. Since no assumption is made about the form of the parent population and the parameter so they may be used under very general conditions. In fact, the specification of the population may not be apply. It does not require complicated sampling theory. It has greater range of applicability because of milder assumptions. Disadvantage: This test cannot be used the parameter of population. These tests is less reliable, less consistent and less powerful than parametric test. Lot of table are needed for these tests. In these tests, many times lot of information are discarded or unused.

What are parametric and non-parametric test? Write some advantage and disadvantage of non-parametric test.

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What are parametric and non-parametric test? Write some advantage and disadvantage of non-parametric test.

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