mwwtest

Mann-Whitney-Wilcoxon non parametric test for two unpaired groups.

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Actualizado 26 Apr 2018

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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

Citar como

Giuseppe Cardillo (2023). mwwtest (https://github.com/dnafinder/mwwtest), GitHub. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2014b
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux

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Versión Publicado Notas de la versión
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

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.