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 selection criteria 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, 8th edition, Volume 2. Basle: Ciba-Geigy Limited.

See also

• Signed rank sum test (one sample)
• Wilcoxon test (paired samples)

External links

• Mann–Whitney U on Wikipedia.