METHODS OF DATA ANALYSIS
PARAMETRIC AND NON PARAMETRIC TESTS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Data are paired
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Sample sizes are small
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The assumption of normality is not met
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Sample is dependent
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Detailed explanation-1: -The Mann–Whitney U test is preferable to the t-test when the data are ordinal but not interval scaled, in which case the spacing between adjacent values of the scale cannot be assumed to be constant.
Detailed explanation-2: -The Mann-Whitney U test is the nonparametric equivalent of the two sample t-test. While the t-test makes an assumption about the distribution of a population (i.e. that the sample came from a t-distributed population), the Mann Whitney U Test makes no such assumption.
Detailed explanation-3: -If your data is following non-normal distribution, then you must go for Mann whitney U test instead of independent t test. It depends on what kind of hypothesis you want to test. If you want to test the mean difference, then use the t-test; if you want to test stochastic equivalence, then use the U-test.