# Mann-Whitney test (independent samples)

Command: | Statistics Rank sum tests Mann-Whitney test (independent samples) |

## Description

The Mann-Whitney test is the non-parametric equivalent of the independent samples t-test. It should be used when the sample data are not Normally distributed, and they cannot be transformed to a Normal distribution by means of a logarithmic transformation.

## Required input

Select the variables for sample 1 and sample 2. You can use the button to select variables and filters in the variables list.

## Results

The Mann-Whitney test (independent samples) combines and ranks the data from sample 1 and sample 2 and calculates a statistic on the difference between the sum of the ranks of sample 1 and sample 2.

When either or both sample sizes are large (>20) then MedCalc uses the Normal approximation (Lentner, 1982) to calculate the P-value. For small sample sizes, in the absence of ties, MedCalc calculates the exact probability (Conover, 1999).

If the resulting P-value is small (P<0.05) then a statistically significant difference between the two samples can be accepted.

## Literature

- Conover WJ (1999) Practical nonparametric statistics, 3
^{rd}edition. New York: John Wiley & Sons. - Lentner C (ed) (1982) Geigy Scientific Tables, 8
^{th}edition, Volume 2. Basle: Ciba-Geigy Limited.

## See also

- To perform different tests in one single procedure, see Comparison of independent samples
- Signed rank sum test (one sample)
- Wilcoxon test (paired samples)

## External links

- Mann-Whitney U on Wikipedia.