# HOW TO RUN MANN WHITNEY U TEST IN SPSS

## What is the Mann Whitney U Test?

Using Man Whitney U Test Statistic in Research

This guide will explain, step by step, how to run the Mann-Whitney U Test in SPSS software by using an example.

The Mann–Whitney U test is a popular test for comparing two independent samples. That is to say,  It is a nonparametric test, as the analysis is undertaken on the rank order of the scores and so does not require the assumptions of a parametric test. (Source)

The Mann-Whitney U test is a nonparametric test (data are not normally distributed). In other words, we use a Mann-Whitney test to determine whether there is a difference in a continuous variable between two independent groups (categorical variable). For example, we want to compare whether there is a difference in IQ score (continuous variable) between male and female students (categorical variable).

Assumptions for the Mann-Whitney U Test

The only assumptions for carrying out a Mann-Whitney test are that the two groups must be independent so that the dependent
variable is ordinal or numerical (continuous). However, in order to report the difference between groups as medians, the shape of the distributions of the dependent variable by the group must be similar. Certainly, it doesn’t matter if the distributions have a different location on the x-axis, they just have to be a similar shape. (Source-PDF)

The Mann Whitney U test is often used when the assumptions of the t-test have been violated. Thus it is useful if:

• The dependent variable is ordinally scaled instead of interval or ratio.
• The assumption of normality has been violated in a t-test (especially if the sample size is small.)
• The assumption of homogeneity of variance has been violated in a t-test

An Example for Man Whitney U Test

We wanted to examine whether there is a difference between a male and a female student on the Math test score. Therefore, we collected data from 25 students. The math test score is our dependent variable; gender is our independent variable with two groups (male, female).

Null hypothesis:

There is no difference in the Math test score between males and females.

Alternative hypothesis:

There is a difference in Math test scores between males and females.

Please watch the SPSS video Tutorial on how to run the Mann-Whitney U Test in SPSS.

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## How to Run Mann Whitney U Test in SPSS: Explanation Step by Step

### In the new window, we should define groups.

If you do not remember how you coded variable, right-click on the variable in the Grouping Variables box (step 2) and click on Variable information. We coded variable Gender 1 for Male, 2 for female, so we will write 1 for Group 1, and 2 for Group 2. Click Continue.

### We will return to the previous window. Click on Options… tab and a new window will open.

In the statistics box, check Descriptive and Quartiles. Click Continue and OK.

## How to report a Mann Whitney U Test results: Explanation Step by Step

### How to Report Descriptive Statistics Table in SPSS Output?

The first table shows descriptive statistics (number of observations, mean, standard deviation, minimum, maximum, percentiles).

### How to Report Ranks Table in SPSS Output?

The second table shows Ranks – number of observations in each group (male and female), mean rank, and sum of ranks for the two groups (male and female). The group with higher rank has the highest Math test score.

### How to Report P-Value for Mann Whitney U Test in SPSS Output?

The third table shows test Statistics. We used Mann-Whitney U test statistics (53.000) and Asymp. Sig. (2-tailed) to reject or fail to reject the null hypothesis.

If p > 0.05, we fail to reject the null hypothesis.

If p < 0.05, we must reject the null hypothesis.

Since in our example, p = 0.173 > 0.05, we fail to reject the null hypothesis and conclude that there is no difference in the Math test score between males and females.

## How to Interpret a Mann Whitney U Test Results in APA Style?

Mann-Whitney U test was conducted to determine whether there is a difference in Math test scores between males and females. The results indicate non-significant difference between groups, [U = 53.00, p = .173]. In conclusion, We fail to reject the null hypothesis and conclude that there is no difference in the Math test score between males and females.

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