Statistical Tests: How to Choose between Parametric & Non Parametric Tests for analyzing the data

Published: 01 January 1970
on channel: Bio-Resource
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#Parametrictest #Nonparametrictest
This video explains about Statistical Tests: How to Choose between Parametric & Non Parametric Tests for analyzing the data

With the availability of statistical software, performing statistical analysis has become very easy.

Choosing the right statistical test for the study can be confusing.

The choice depends on :
1. Nature of the data,
2. Does the data follow normal distribution or not, and
3. What is the study hypothesis.

To decide which test to use for analysing the data, consider the research question first and make sure that it allows for a parametric or nonparametric test procedure.

Then choose between these two depending on how you want to answer your research question.

A parametric test is a type of statistical test that makes assumptions about the parameters of the population distribution(s) from which the sample has been drawn. If the information is completely known through its parameters then the test is called a parametric test.

Nonparametric tests are usually referred as distribution‑free tests.

A nonparametric statistical test is the one that does not necessitate any conditions to be fulfilled about the parameters of the population from which the sample was drawn.

Advantages & Disadvantages of Parametric & Non Parametric Tests


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