Mann Whitney Test In Excel How To Work Your

The chart on the left shows the distribution of male and female engagement scores having the same shape, but a different location (i.e., the female scores are shifted to the right).

The first three relate to your choice of study design, whilst the fourth reflects the nature of your data.

Examples of continuous variables include revision time (measured in hours), intelligence (measured using IQ score), exam performance (measured from 0 to 100), weight (measured in kg), and so forth.

Examples of ordinal variables include Likert items (e.g., a 7-point scale from strongly agree through to strongly disagree), amongst other ways of ranking categories (e.g., a 5-point scale explaining how much a customer liked a product, ranging from Not very much to Yes, a lot).

Example independent variables that meet this criterion include gender (two groups: males or females), employment status (two groups: employed or unemployed), transport type (two groups: bus or car), smoker (two groups: yes or no), trial (two groups: intervention or control), and so forth.

However, when you run the Mann-Whitney U test procedure in SPSS, you will need to decide which two groups you want to compare (e.g., you could compare bus and car, or bus and plane, and so forth).

For example, there must be different participants in each group with no participant being in more than one group.

This is more of a study design issue than something you can test for, but it is an important assumption of the Mann-Whitney U test.

If your study fails this assumption, you will need to use another statistical test instead of the Mann-Whitney U test (e.g., a Wilcoxon signed-rank test ).

This will determine how you interpret the results of the Mann-Whitney U test.

Mann Whitney Test In Excel How To Work Your

Since this is a critical assumption of the Mann-Whitney U test, and will affect how to work your way through this guide, we discuss this further in the next section.

However, it is not often that the test is directly interpreted in this way.

However, this is not so much a choice that you make, but is based on whether the distribution of scores for both groups of your independent variable (e.g., the distribution of scores for males and the distribution of scores for females for the independent variable, gender) have the same shape or a different shape.

However, if the two distributions are the same shape, the Mann-Whitney U test is used to determine whether there are differences in the medians of your two groups.

We discuss these two different approaches to using the Mann-Whitney U test in turn.

Using this interpretation of the Mann-Whitney U test, we would wish to know whether male and female engagement scores are similar or whether one gender has higher or lower values than the other.

An example of similar engagement scores and dissimilar engagement scores can be seen in the diagrams shown below.

The Mann-Whitney U test can do this determine whether the values in one group are lower or higher than the values in the other group (e.g., females higher than males) by comparing the mean ranks of each distribution of scores (e.g., males and females engagement scores).

The ranks obtained for males are then averaged, as are the females ranks.

This results in a mean rank for males and a mean rank for females.

If the distributions are identical, which is the null hypothesis of the Mann-Whitney U test, the mean rank will be the same for both males and females.

However, if one group (e.g., females) tends to have higher values than the other group, that groups scores will have been assigned higher ranks and will have a higher mean rank (and vice-versa for the group with lower scores).

It is this difference in mean rank that is tested by the Mann-Whitney U test for statistical significance.

Using this approach, different distributions of scores can be accommodated by the Mann-Whitney U test when determining whether values (i.e., via mean ranks) are different between two groups, as shown below.

Mann Whitney Test In Excel For Mac