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Do you need normal distribution for Mann-Whitney U test?
The Mann-Whitney U test is used to compare differences between two independent groups when the dependent variable is either ordinal or continuous, but not normally distributed. You can access this enhanced Mann-Whitney U test guide by subscribing to Laerd Statistics.
When do you not use a Mann-Whitney U test?
If one desires a simple shift interpretation, the Mann–Whitney U test should not be used when the distributions of the two samples are very different, as it can give erroneous interpretation of significant results. In that situation, the unequal variances version of the t-test may give more reliable results.
Is the Mann Whitney U test the same as independent samples?
This would be more in keeping with the Mann-Whitney U test being used as an alternative to the independent-samples t-test (i.e., both would then use a measure of central tendency: the ‘mean’ for the independent-samples t-test and the ‘median’ for the Mann-Whitney U test).
How can a Mann-Whitney U-test return a P = 1.00?
I am running the U-test to account for unequal group sizes and non-normal data on several different variables, but is a z-statistic of .000 and P value of 1.00 accurate to report? Thanks in advance. How can a Mann-Whitney U-Test return a p = 1.00 for unequal means? Because it’s not a test for means.
What is the critical value of Mann Whitney U?
Using n1 = 8 and n2 = 7 with a significance level of .01, the Mann-Whitney U Table tells us that the critical value is 6: Since our test statistic (12) is greater than our critical value (6), we fail to reject the null hypothesis. 5. Interpret the results.
What happens to statistical power when sample sizes are unequal?
Note however, that your statistical power (i.e., the ability to detect a difference that really is there) will diminish as the group sizes become more unequal. For an example, I have a simulation (actually of a t-test, but the principle is the same) that demonstrates this here.