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Parametric andNonparametric Test

By:Sai Prakash

MBA InsuranceManagementPondicherry University

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∗ If there is no knowledge about the population or

paramters, but still it is re#uired to test thehypothesis of the population$ "hen it is callednon-parametric test

∗ Eg: mann-%hitney, rank sum test, &ruskal-%allistest

Nonparametric test

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Classication !" hypothesis

Parametric testNon Parametric test

t# test$ "#test$ %#test$ AN!&Amann#'hitney$ ranksum test$ (ruskal#

'allis test

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'i(erence between parametric and Nonparametric

Parametric Non Parametric

Information about population is

completely known

No information about the

population is a)ailable

*peci+c assumptions are maderegarding the population

No assumptions are maderegarding the population

Null hypothesis is made onparameters of the populationdistribution

 "he null hypothesis is free fromparameters

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'i(erence between parametric andNon parametric

Parametric Non Parametric

 "est statistic is based on thedistribution

 "est statistic is arbritary

!arametric tests are applicable onlyfor )ariable

It is applied both )ariable andartributes

No parametric test ecist forNorminal scale data Non parametric test do eist fornorminal and ordinal scale data

!arametric test is powerful, if iteist

It is not so powerful like parametrictest

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∗  Non parametric test are simple and easy to

understand∗ It will not in)ol)e complecated sampling theory

∗ No assumption is made regarding the parentpopulation

∗ "his method is only a)ailable for norminal scaledata

∗ "his method are easy applicable for artribute dates$

Ad)antages of non parametric test

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∗  it can be applied only for norminal or ordinal

scale∗ or any problem, if any parametric test eist it is

highly powerful$

∗ Nonparametric methods are not so e.cient as of

parametric test

∗ No nonparametric test a)ailable for testing theinteraction in analysis of )ariance model$

'isad)antages of non parametric test

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 "hank you$$$$