The Mann-Whitney U test is used to compare differences between two independent groups on an dependent variable, but not normally distributed. The test does not assume any properties regarding the distribution of the dependent variable in the analysis.

Mann Whitney test is for data measured on an ordinal scale. It is easy to judge if your data is ordinal as you should be able to rank order it without knowing the difference between these ranks. Mann whitney test can then use data from two separate samples to evaluate the difference between two populations. It can be thought of as an alternative to independent-measures t hypothesis test.

A real difference between populations is reflected in the larger ranks of one sample. The null hypothesis is that there is no difference between the two populations. In other words, the ranks will not be systematically higher or lower. You can easily run this test if you have access to SPSS.

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. For example, you could use the Mann-Whitney U test to understand whether attitudes towards pay discrimination, where attitudes are measured on an ordinal scale, differ based on gender (i.e., your dependent variable would be "attitudes towards pay discrimination" and your independent variable would be "gender", which has two groups: "male" and "female"). Alternately, you could use the Mann-Whitney U test to understand whether salaries, measured on a continuous scale, differed based on educational level (i.e., your dependent variable would be "salary" and your independent variable would be "educational level", which has two groups: "high school" and "university"). The Mann-Whitney U test is often considered the non-parametric alternative to the independent t-test although this is not always the case.

Thank you Dear colleagues for your responses, all of them will be very helpful for our research.