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Assumption of normality and independence in independent t-test

5 years ago in Data Analysis By Shreya K

Data analysis

I want to know about assumption of normality and independence in independent t-test. Any explanation?

All Answers (3 Answers In All)

By Raj Shravan Answered 5 years ago

The data is independent of each other. I.e. the data of one participant is not systematically related to that of the other participant. This is assumption of independence. The test variable will be distributed within each of the two populations. This is known as the assumption of normality.

By Payal G Answered 5 years ago

One of the assumptions of independent t-test is the assumption of independence. It is dealt when a study is set up. The assumption of independence is known as unforgiving assumption. It means that if two groups are not independent of each other, then one cannot use this test. Although if violated, the independence assumption can spoil your study, there is no other way to use the sample data of the study to test the validity of this prerequisite condition.

By Nithin Rao Answered 5 years ago

Payal has explained about assumption of independence, here I will explain about assumption of normalityIn the assumption of normality, there is no major departure from normality, like retaining the null hypothesis indicating that the normality assumption has been met for the given sample. The alternative hypothesis is that there is a critical departure from normality, like rejecting the null hypothesis in the approval of alternative hypothesis indicating that the normality assumption has not been met for the given sample.