mwwtest
This file execute the non parametric Mann-Whitney-Wilcoxon test to evaluate the
difference between unpaired samples. If the number of combinations is less than
20000, the algorithm calculates the exact ranks distribution; else it
uses a normal distribution approximation. The result is not different from
RANKSUM MatLab function, but there are more output informations.
There is an alternative formulation of this test that yields a statistic
commonly denoted by U. Also the U statistic is computed.
Syntax: STATS=MWWTEST(X1,X2)
Inputs:
X1 and X2 - data vectors.
Outputs:
- T and U values and p-value when exact ranks distribution is used.
- T and U values, mean, standard deviation, Z value, and p-value when
normal distribution is used.
If STATS nargout was specified the results will be stored in the STATS
struct.
Example:
X1=[181 183 170 173 174 179 172 175 178 176 158 179 180 172 177];
X2=[168 165 163 175 176 166 163 174 175 173 179 180 176 167 176];
Calling on Matlab the function: mwwtest(X1,X2)
Answer is:
MANN-WHITNEY-WILCOXON TEST
Group_1 Group_2
_______ _______
Numerosity 15 15
Sum_of_Rank_W 270 195
Mean_Rank 18 13
Test_variable_U 75 150
Sample size is large enough to use the normal distribution approximation
Mean SD Z p_value_one_tail p_value_two_tails
_____ ______ ______ ________________ _________________
112.5 24.047 1.5386 0.061947 0.12389
Created by Giuseppe Cardillo
giuseppe.cardillo-edta@poste.it
To cite this file, this would be an appropriate format:
Cardillo G. (2009). MWWTEST: Mann-Whitney-Wilcoxon non parametric test for two unpaired samples.
http://www.mathworks.com/matlabcentral/fileexchange/25830
Citation pour cette source
Giuseppe Cardillo (2024). mwwtest (https://github.com/dnafinder/mwwtest), GitHub. Récupéré le .
Compatibilité avec les versions de MATLAB
Plateformes compatibles
Windows macOS LinuxCatégories
- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > ANOVA >
- Industries > Biotech and Pharmaceutical > ROC - AUC >
- Computational Finance > Datafeed Toolbox > Financial Data > Trading Technologies >
Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Découvrir Live Editor
Créez des scripts avec du code, des résultats et du texte formaté dans un même document exécutable.
Les versions qui utilisent la branche GitHub par défaut ne peuvent pas être téléchargées
Version | Publié le | Notes de version | |
---|---|---|---|
2.0.0.0 | inputparser; table implementation; github link |
|
|
1.4.0.0 | more clear output; improvement in computations |
||
1.3.0.0 | Changes in description |
||
1.2.0.0 | bug fixed in T computation when n2<n1 |
||
1.1.0.0 | change in the help section |
||
1.0.0.0 |