parametric and nonparametric test. parametric test if the information about the population is...

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PARAMETRIC AND NONPARAMETRIC TEST

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Page 1: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical

PARAMETRIC AND NONPARAMETRIC TEST

Page 2: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical

Parametric Test

If the information about the population is completely known by means of its parameters then statistical test is called parametric test

Eg: t- test, f-test, z-test, ANOVA

Page 3: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical

Nonparametric test

If there is no knowledge about the population or paramters, but still it is required to test the hypothesis of the population. Then it is called non-parametric test

Eg: mann-Whitney, rank sum test, Kruskal-Wallis test

Page 4: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical

Classification Of hypothesis

Parametric test Non Parametric test

t- test, f-test, z-test, ANOVAmann-Whitney, rank sum test, Kruskal-

Wallis test

Page 5: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical

Difference between parametric and Non parametric

Parametric Non Parametric

Information about population is completely known

No information about the population is available

Specific assumptions are made regarding the population

No assumptions are made regarding the population

Null hypothesis is made on parameters of the population distribution

The null hypothesis is free from parameters

Page 6: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical

Difference between parametric and Non parametric

Parametric Non Parametric

Test statistic is based on the distribution

Test statistic is arbritary

Parametric tests are applicable only for variable

It is applied both variable and artributes

No parametric test excist for Norminal scale data

Non parametric test do exist for norminal and ordinal scale data

Parametric test is powerful, if it exist

It is not so powerful like parametric test

Page 7: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical
Page 8: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical

Advantages of non parametric test

Non parametric test are simple and easy to understand

It will not involve complecated sampling theory No assumption is made regarding the parent

population This method is only available for norminal scale

data This method are easy applicable for artribute dates.

Page 9: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical

Disadvantages of non parametric test

it can be applied only for norminal or ordinal scale

For any problem, if any parametric test exist it is highly powerful.

Nonparametric methods are not so efficient as of parametric test

No nonparametric test available for testing the interaction in analysis of variance model.

Page 10: PARAMETRIC AND NONPARAMETRIC TEST. Parametric Test  If the information about the population is completely known by means of its parameters then statistical

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