- Il test di Wilcoxon e il test di Mann-Whitney (anche noto come test U di Mann-Whitney) sono due dei più potenti test non parametrici per verificare, in presenza di valori ordinali provenienti da una distribuzione continua, se due campioni statistici provengono dalla stessa popolazione.. Il test di Wilcoxon e il test di Mann Whitney sono due test non parametrici diversi: il primo è per.
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**Mann-Whitney****U****test**(sometimes called the Wilcoxon rank-sum**test**) is used to compare the differences between two independent samples when the sample distributions are not normally distributed and the sample sizes are small (n <30). It is considered to be the nonparametric equivalent to the two-sample independent t-test.. Here are some examples of when you might use a**Mann-Whitney****U****test** - Mann-Whitney U Test Calculator Two random, independent samples The data is continuous - in other words, it must, in principle, be possible to distinguish between values at the nth... Scale of measurement should be ordinal, interval or ratio For maximum accuracy, there should be no ties, though this.
- Mann-Whitney U test and Wilcoxon rank-sum test are also often used to identify association between taxa or OTUs and covariates. However, these approaches conduct the association analysis based on the ranks of observed relative abundances, resulting in information loss and high false-negative rates
- e if 2 groups are significantly different from each other on your variable of interest. Your variable of interest should be continuous and your 2 groups should have similar values on your variable of interest

Il test U di Mann - Whitney verifica un'ipotesi nulla secondo cui la probabilità che un'osservazione estratta a caso da un gruppo sia maggiore di un'osservazione estratta a caso dall'altro è uguale a 0,5 contro un'alternativa che questa probabilità non sia 0,5 (vedere Mann-Whitney U test # Assunzioni e formulazione formale di ipotesi) ** C - continuity correction, when U > μ: C = -0**.5, when U < μ: C = 0.5 Target Unlike t-test that compares the means, the Mann-Whitney U test compares a randomly selected value from group1 to a randomly selected value from group2. When the two distributions have a similar shape you can use the test to compare also the medians

Il test mann-Whitney utilizzando i ranghi ed è più informativo e completo del test semplice della mediana che valuta solo il numero di casi sopra o sotto questa misura di posizione. Le assunzioni che sottostanno il test sono ridotte rispetto ai test parametrici ( Z e t): • i due. • E' un test non parametrico molto spesso usato per controllare se due campionamenti provengono dalla stessa popolazione. • E' l'analogo non-parametrico del test t di Student per campioni indipendenti. • Il test e' normalmente definito con la sigla U . Test di Mann-Whitney • E' uno dei test non parametrici più potenti e serve The Mann-Whitney U test is often considered the nonparametric alternative to the independent t-test although this is not always the case. Unlike the independent-samples t-test, the Mann-Whitney U test allows you to draw different conclusions about your data depending on the assumptions you make about your data's distribution

Der Mann-Whitney-U-Test basiert auf der Idee der Rangierung der Daten. Das heisst, es wird nicht mit den Messwerten selbst gerechnet, sondern diese werden durch Ränge ersetzt, mit welchen der eigentliche Test durchgeführt wird The Mann Whitney U test, sometimes called the Mann Whitney Wilcoxon Test or the Wilcoxon Rank Sum Test, is used to test whether two samples are likely to derive from the same population (i.e., that the two populations have the same shape) The Mann-Whitney U test is also known as the Mann-Whitney-Wilcoxon, Wilcoxon-Mann-Whitney, and the Wilcoxon Rank Sum. A Mann-Whitney U test is typically performed when each experimental unit, (study subject) is only assigned one of the two available treatment conditions. Thus, the treatment groups do not have overlapping membership and are. * A good example of a non-parametric test is the Mann-Whitney U-test (Also known as the Mann-Whitney-Wilcoxon (MWW) or Wilcoxon Rank-Sum Test)*. Unlike its parametric counterpart, the t-test for two samples, this test does not assume that the difference between the samples is normally distributed, or that the variances of the two populations are equal

In this video tutorial, I will explain how to perform a Mann-Whitney U test in GraphPad Prism. I will also show you how to interpret the results. THE ONLINE. In fact, if the total sample size is seven or less, the Mann-Whitney test will always give a P value greater than 0.05 no matter how much the groups differ. Mann-Whitney U and U' Prism reports the value of the Mann-Whitney U value, in case you want to compare calculations with those of another program or text A Mann-Whitney U test (sometimes called the Wilcoxon rank-sum test) is used to compare the differences between two independent samples when the sample distributions are not normally distributed and the sample sizes are small (n <30). It is considered to be the nonparametric equivalent to the two-sample independent t-test. This tutorial explains how to perform a Mann-Whitney U test in R Mann-Whitney-U-Test Einführung in den Mann-Whitney-U-Test. Der Mann-Whitney-U-Test (auch Wilcoxon-Mann-Whitney-Test, Wilcoxon-Rangsummentest oder einfach nur U-Test genannt) ist eine nicht-parametrische Alternative zu dem ungepaarten t-Test.Der Mann-Whitney-U-Test wird verwendet, um zu überprüfen, ob zwei unabhängige Stichproben aus derselben Grundgesamtheit stammen (für gepaarte.

Ein Mann-Whitney-U-Test (manchmal auch als Wilcoxon-Rang-Summen-Test bezeichnet) wird verwendet, um die Unterschiede zwischen zwei unabhängigen Proben zu vergleichen, wenn die Probenverteilungen nicht normal verteilt sind und die Probengrößen klein sind (n <30). Es wird als nichtparametrisches Äquivalent zum unabhängigen t-Test mit zwei Stichproben angesehen Note that the Mann-Whitney test is unusual in this respect: normally, the BIGGER the test statistic, the less likely it is to have occurred by chance). This handout deals with using the Mann-Whitney test with small sample sizes. If you have a large number of participants, you can convert U into a z-score and look this up instead

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- Why Use Mann-whitney U-test - Free download as Word Doc (.doc), PDF File (.pdf), Text File (.txt) or read online for free. fre
- Mann Whitney U - Free download as Powerpoint Presentation (.ppt / .pptx), PDF File (.pdf), Text File (.txt) or view presentation slides online. Geography Aleve
- // Mann-Whitney-U-Test - Voraussetzungen, Funktionsweise und Interpretation //Sofern man zwei unabhängige Stichproben hat und sie mittels metrisch skalierter..
- Mann-Whitney-U-Test Mann-Whitney-U-Test: Hypothesen. Auch wenn der Mann-Whitney-U-Test als direkte Alternative zum ungepaarten t-Test verwendet wird, hat er doch komplett andere Hypothesen. Dies wird auch durch die vierte Voraussetzung deutlich, dass die Verteilungsform zwischen den beiden Gruppen (etwa) gleich sein sollte.. Ursprünglich wurde der Test von Mann und Whitney (1947) entwickelt.
- e the difference between two groups of either continuous or ordinal data. The reason you would perform a Mann-Whitney U test over an independent t-test is when the data is not normally distributed

A Mann-Whitney U-test (also called the rank-sum test, or Wilcoxin-Mann-Whitney test) uses sample data to test if a numeric outcome variable with any distribution differs across two independent groups. This test is an alternative to the two-sample independent t-test when the data fails the normality assumption or if the sample sizes in each group are too small to assess normality The Mann-Whitney U test is based on the common rank ordering according to ascending magnitude of all observations from two samples, say A with size N 1 and B with size N 2, and counts for each observation from B by how many observations from A it is preceded; test statistic U equals the sum of these counts (for simplicity, we ignore the possibility of ties) * Mann-Whitney U-Test Assumptions:*. Hypotheses:. Ho: The population distributions in the two groups are the same. HA: The population distributions in the... Example 1: Hand calculation video. In this video, we'll use a Mann-Whitney U -test to see if the distribution of weights... Example 2: How to. The Mann Whitney U statistic is defined as: - where samples of size n 1 and n 2 are pooled and R i are the ranks. U can be resolved as the number of times observations in one sample precede observations in the other sample in the ranking. Wilcoxon rank sum, Kendall's S and the Mann-Whitney U test are exactly equivalent tests SPSS Mann-Whitney Test - Output Significance Tests. Some of the output shown below may be absent depending on your SPSS license and the sample size: for n = 40 or fewer cases, you'll always get some exact results. Mann-Whitney U and Wilcoxon W are our test statistics; they summarize the difference in mean rank numbers in a single number

Mann-Whitney Non Parametric U Test. The preferred non-parametric method for unpaired samples is the Mann-Whitney non parametric hypothesis test or Mann-Whitney test (it is also called as Wilcoxon Rank Sum Test or the Mann Whitney Wilcoxon Test) and thus the non parametric solution to evaluating two independent datasets comparable to the Student's T test This online calculator performs the Mann-Whitney U test (also called the Mann-Whitney-Wilcoxon (MWW), Wilcoxon rank-sum test, or Wilcoxon-Mann-Whitney test). person_outline Timur schedule 2018-08-12 11:02:47. As it was stated in Two sample t-Test, you can apply the t-test if the following assumptions are met U-test di Mann-Whitney: intervallo di confidenza per la dimensione dell'effetto. Secondo Fritz, Morris e Richler (2011; vedi sotto), può essere calcolato come una dimensione dell'effetto per il test U di Mann-Whitney usando la formula r = zr r Questo è conveniente per me, poiché riporto r anche in altre occasioni * TEST U di MANN-WHITNEY*. Confronto di dati ordinali. Il test U è adatto al confronto di due serie di dati ordinali. Ad esempio due serie di punteggi assegnati in un test: Serie A : 90,76,88,70,77,64. Serie B: 83,91,74,65,8

- Il test di Wilcoxon-Mann-Whitney (o test di Wilcoxon della somma dei ranghi) si applica nel caso in cui si chiede di confrontare le medie dei valori di due gruppi che non seguono una distribuzione normale. È l'equivalente del test t per campioni indipendenti. Vediamo come risolvere il problema con R: > a = c(6, 8, 2, 4, 4, 5) > b = c(7, 10, 4, 3, 5, 6
- The Mann-Whitney test compares the medians from two populations and works when the Y variable is continuous, discrete-ordinal or discrete-count, and the X variable is discrete with two attributes. Of course, the Mann-Whitney test can also be used for normally distributed data, but in that case it is less powerful than the 2-sample t-test.. Uses for the Mann-Whitney Test
- Statistics: 2.3 The Mann-Whitney U Test Rosie Shier. 2004. 1 Introduction The Mann-Whitney U test is a non-parametric test that can be used in place of an unpaired t-test. It is used to test the null hypothesis that two samples come from the same population (i.e. have the same median) or, alternatively, whether observations in on
- 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. The Mann-Whitney U test is a nonparametric test (data are not normally distributed)
- Wilcoxon-Mann-Whitney as an alternative to the t-test. September 8, 2017. April 12, 2014 by Jonathan Bartlett. The two sample t-test is one of the most used statistical procedures. Its purpose is to test the hypothesis that the means of two groups are the same. The test assumes that the variable in question is normally distributed in the two.

The Mann-Whitney U test can be considered equivalent to the Kruskal-Wallis test with only two groups. Mood's median test compares the medians of two groups. It is described in its own chapter. For ordinal data, an alternative is to use cumulative link models, which are described later in this book ∗Test non parametrici basati sui ranghi Procedimento di calcolo del test di Mann-Whitney. diap. 13.5 Ricapitolando, il procedimento per il calcolo del test di Mann-Whitney per la verifica dell'ipotesi che un trattamento non abbia effetto, consiste nei seguenti passi: ØAttribuire un rango a tutte le osservazioni sulla base della loro grandezza This online calculator provides an implementation to solve the exact permutation of the Wilcoxon-Mann-Whitney test, using the Wilcoxon rank-sum test. The exact solution is provided for tied and non-tied data sets. In order to start the test, enter your sample data (use whitespaces to separate the elements), choose the test variant and click the.

First of all it might be useful to remember that Mann-Whitney test is also called Wilcoxon rank-sum test. Since it is the same test there is no need to explain the difference ;) A good answer to the common question about the difference between W statistic and U statistic is given here: Is the W statistic output by wilcox.test() in R the same as the U statistic 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 In statistics, the Mann-Whitney U test (also called Wilcoxon rank-sum test) is a nonparametric test of the null hypothesis that it is equally likely that a randomly selected value from one population will be less than or greater than a randomly selected value from a second population. This test can be used to investigate whether two independent samples were selected from populations having.

Mann-Whitney U Test Calculator. Note: You can find further information about this calculator, here. Enter your sample values into the text boxes below, either one score per line or as a comma delimited list. Sample 1. Sample 2. Significance Level: .01 Using Mann-Whitney U test (Wilcoxon rank sum test), I am comparing two groups to see whether they are statistically different. Based on almost the same median and mean values between the two groups, I definitely thought that p-value would be very high. But P-value was < 0.0001 (attached). Any i.. 1.3. The **Test** The **Mann‐Whitney** **U** **test** initially implies the calculation of a **U** statistic for each group. These statistics have a known distribution under the null hypothesis identified by **Mann** and **Whitney** (1947) (see Tables 3 to 8). Mathematically, the **Mann‐Whitney** **U** statistics ar In statistics, the Mann-Whitney U test (also called the Mann-Whitney-Wilcoxon (MWW), Wilcoxon rank-sum test, or Wilcoxon-Mann-Whitney test) is a non-parametric test for assessing whether two independent samples of observations have equally large values. It is one of the best-known non-parametric significance tests. It was proposed initially by Frank Wilcoxon in 1945, for equal sample. You can access our enhanced Mann-Whitney U test guide, as well as all of our SPSS Statistics content, by subscribing to Laerd Statistics, or learn more about our enhanced content in general on our Features: Overview page. Join the 10,000s of students, academics and professionals who rely on Laerd Statistics

The Mann-Whitney U test is essentially an alternative form of the Wilcoxon Rank-Sum test for independent samples and is completely equivalent.. Define the following test statistics for samples 1 and 2 where n 1 is the size of sample 1 and n 2 is the size of sample 2, and R 1 is the adjusted rank-sum for sample 1 and R 2 is the adjusted rank-sum of sample 2. It doesn't matter which sample is. The Mann‐Whitney U test, which is also known as the Wilcoxon rank sum test, tests for differences between two groups on a single, ordinal variable with no specific distribution (Mann & Whitney, 1947; Wilcoxon, 1945). In contrast, the independent samples t‐test, which is also a test of two groups, requires the single variable to be measured. The Mann-Whitney and the Kolmogorov-Smirnov tests are nonparametric tests that compares the distributions of two unmatched groups The Mann-Whitney U is one of these tests. In the following work, a summary of this test is presented. The explanation of the logic underlying this test and its application are presented

Hi i am Arun, i am using pspp 079. 32 bit. I need to use Mann whitney u test for data analysis. i couldn't find it on my pspp version. Is it available on pspp. can anybody help me. thank you. arun. John Darrington. 2012-05-16 18:13:09 UTC. Permalink The advantage of using the Mann-Whitney U test is that it has no effect because of the outliers as it considers the median instead of the mean for the test. Steps for Performing the Mann Whitney U test: Collect two samples and sample 1 and sample 2. Take the first observation from sample 1 and compare it with observations in sample 2 Nonparametric Tests of Group Differences . R provides functions for carrying out Mann-Whitney U, Wilcoxon Signed Rank, Kruskal Wallis, and Friedman tests. # independent 2-group Mann-Whitney U Test wilcox.test(y~A) # where y is numeric and A is A binary factor # independent 2-group Mann-Whitney U Test The Mann-Whitney U Test is a nonparametric test that can be substituted for the two-sample t-Test (both pooled or unpooled) when the following circumstances occur: 1) Normality of at least one sample or one population cannot be verified and sample size is small

Mann Whitney U-test Calculator Use this free calculator to compute a Mann-Whitney critical U value . Please input comma separated sets of values in SAMPLE 1 and SAMPLE 2 in the required fields and click CALCULATE Mann-Whitney U test (Non-parametric equivalent to independent samples t-test) The Mann-Whitney U test is used to compare whether there is a difference in the dependent variable for two independent groups. It compares whether the distribution of the dependent variable is the same for the two groups and therefore from the same population Mann Whitney test (also known as Wilcoxon rank sum test): The Mann Whitney Test Wiki is an excellent source of its history and background, as well as its statistical theory. Its advantage over the unpaired t-test is that it does not require the unpaired data samples to come from a normally distributed populations In this guide, I will explain how to perform a Mann-Whitney U test in GraphPad Prism. I will also show you how to interpret and report the results. Assumptions of a Mann-Whitney U test. Before performing the test, it is important to check that your data satisfies the assumptions of a Mann-Whitney U test

I am looking for a few rules of thumb of when to determine that my data is 'normal enough' to use a t-test vs. a Mann-Whitney U-test. From what I have read, most real world data sets are non-normal, and when sample sizes are large, tests including the Shaprio-Wilk will always reject the null hypothesis Mann-Whitney U Test with the Python Package Pingouin. As previously mentioned, we can also install the Python package Pingouin to carry out the Mann-Whitney U test. Here's how to perform this test with the mwu() method: from pingouin import mwu results2 = mwu(df['Notrt'], df['Trt'], tail= 'one-sided') Code. The MannWhitney U Test is used to analyse whether two data samples are significantly different - from one another or whether any differences witnessed by the researcher are there simply due to chance. Why would we use the Mann-Whitney U test? Researchers who are interested in how similar two sets of data are, rather than if there is The Mann-Whitney U test was applied to test if there were differences in engagement score between male and female groups. Since the shapes of distribution of engagement scores for two groups were not similar, we could conclude the engagement scores for fem ales (mean rank = 17.75) and males (mean rank = 23.25) were not statis tically significantly different, U = 145, Z = -1.488, p = 0.142 (>0. The Mann Whitney U-test is a nonparametric test which is used to compare two treatments in clinical trials and for analyzing the difference between the medians of two data sets. It is an alternative of t-test and the major difference between the two is t test is used to analyze population mean and Mann Whitney Test is used for analyzing population median

- Mann-Whitney U-test. The Mann Whitney U--‐test is a member of the bigger group of dependence tests. Dependence tests assume that the variables in the analysis can be split into independent and dependent variables. A dependence test is a test that compares the mean scores of an independent and a dependent variable.It assumes that differences i
- Mann-Whitney U test This is a test that compares the medians of two data sets, to see if there is a significant difference between the data sets. It shows if one of the samples tends to have large values than the other, and therefore shows if there is a difference between the data sets or if any perceived difference is simply due to chance
- The Mann-Whitney U Test What you need to know - Title: Nonparametric tests and ANOVAs: What you need to know Author: Luke Harmon Last modified by: hansonb Created Date: 11/1/2006 10:33:19 PM Document presentation.

The Mann-Whitney test does not always achieve the confidence interval that you specify because the Mann-Whitney statistic (W) is discrete. Minitab calculates the closest achievable confidence level. Estimation for Difference: Difference. CI for Difference. Achieved Confidence-1.8 Ma ora ho condotto un test di Mann-Whitney e non sono sicuro di quali valori presentare. SPSS mi dà un Mann-Whitney , Wilcoxon , e -value. Presento tutti questi 4 valori? O sono irrilevanti? U U W W Z Z P The Mann-Whitney U Test is a popular test for comparing two independent samples. 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 The Mann-Whitney U tests the null hypothesis 'There is no difference between the leg ulcer free weeks for the Clinic group compared to the group receiving the standard treatment'. The null is rejected if the p-value for the t-test is less than 0.05. Use the wilcox.test(dependent~independent).By default it conducts the Mann Whitney U Test

Now the null hypothesis for this Mann-Whitney-U test would just suggest that there is no difference in the medians between the two groups and the alternative hypothesis if it's two tailed, will just say that there is a difference. And the one sided test with one group actually having a median more or less than the other group Key Concept: For any Mann-Whitney U test, the theoretical range of U is from 0 (complete separation between groups, H 0 most likely false and H 1 most likely true) to n 1 *n 2 (little evidence in support of H 1).. In every test, U 1 +U 2 is always equal to n 1 *n 2. In the example above, U can range from 0 to 25 and smaller values of U support the research hypothesis (i.e., we reject H 0 if U. Il test di Mann-Whitney è un test non parametrico che si utilizza per confrontare due campioni indipendenti quando la scala di misurazione dei dati è almeno ordinale. Per capire quando è opportuno utilizzarlo partiamo da un caso di studio. In uno studio epidemiologico si voleva indagare quale fosse il livello di attività fisica dei soggetti ultranovantenni This is an inferential test created by Henry Mann (left) and Donald Whitney (below, left).It is used when: You have a test of difference with independent groups design; The data is at least ordinal level* (* it's easy to turn interval/ratio level data into ordinal data: you just put the scores into rank order) The Edexcel exam might ask you about the appropriateness of the Mann-Whitney U.

Mann Whitney U-test : Application Analysing the traffic flows Analysing the impact of retail development upon traffic and the local area. primary data was collected in two parts. The first part was conducted before the construction of the planned development (sample x) Mann-Whitney U test - Science method Q1: Yes, these constructs are latent variables and therefore a better choice is to use SEM over GLM. If you are not... Q2: No, don't compute a composite score through the mean of the items. Instead, I recommend to obtain the composite..

Mann Whitney U Test 1. Comparing medians: the Man Whitney U-test The Mann Whitney U-test is a fairly complicated statistical test to understand, though it is quite easy to apply to a set of data. So, while the calculation is relatively easy, knowing when to apply it, and what the calculation actually means, is a little more difficult The test was originally proposed by Wilcoxon (1945) and then modified to allow for different sample sizes by Mann & Whitney (1947). There are two commonly used equivalent statistics: the Wilcoxon sum of ranks (S)-statistic and the Mann-Whitney U-statistic

When the variance of two populations is different, then the Mann Whitney test leads to large type 1 error, even when the means are the same. This is expected since the Mann Whitney tests for difference in distributions, not in means. The t test is robust to differences in variance but identical means; Experiment 1) Different means, same variance The Mann-Whitney U-Test in SPSS The research question for our U-Test is as follows: Do the students that passed the exam achieve a higher grade on the standardized reading test? The question indicates that the independent variable is whether the students have passed the final exam or failed the final exam, and the dependent variable is the grade achieved on the standardized reading test (A to F) The Mann‐Whitney U, A Test for Assessing Whether Two Independent Samples Come from the Same Distribution. Tutorials in Quantitative Methods for Psychology 2008; vol. 4(1), p. 13‐20. Klaar met lezen? Je kunt naar het OVERZICHT van alle statistische onderwerpen op deze wiki gaan Mann-Whitney U-Test is a non-parametric test used to compare two independent populations. It tests whether two independent samples originate from the same population. It compares the null hypothesis to the two-sided research hypothesis for differences or similarities. When should you use the test? Th The Mann Whitney U Test, also known as Mann-Whitney-Wilcoxon (MWW) test, is the same a as T-Test, but is used for ordinal (=ranked) data.It is a test of difference between the medians rather than a test of comparison between the means. The test can appear complicated to perform and understand, but is actually very simple to interpret and very useful

THE MANN-WHITNEY U TEST. Stage 1: Call one sample A and the other B. Stage 2: Place all the values together in rank order (i.e. from lowest to highest). If there are two samples of the same value, the 'A' sample is placed first in the rank Mann Whitney U test or Wilcoxon Rank-Sum test, on the other hand, is an analog of the parametric Student's t-test. It compares the means between two independent groups with the assumption that the data is not in a normal distribution. Therefore, it is useful for numerical/continuous variables How to Mann Whitney U Test in SPSS Completed Successfully | Mann Whitney U Test is part of non parametric statistical test that aims to determine whether there is a difference in the average group with independent samples. Mann Whitney U Test is an independent sample t test when the research data is not normally distributed

The Mann-Whitney test, sometimes also called the Wilcoxon-Mann-Whitney test or the Wilcoxon Rank Sum test, is often interpreted to test whether the median of the distributions are the same. Although a difference in median is the dominant differentiator if it is present, other factors such as the shape or the spread of the distributions may also be significant Mann-Whitney U, Sign Test, and Wilcoxon Tests. This tutorial will show you how to use SPSS version 9.0 to perform Mann Whitney U tests, Sign tests and Wilcoxon matched-pairs signed-rank tests on ordinally scaled data. This tutorial assumes that you have: Downloaded the standard class data set (click on the link and save the data file Asyms. Sig. (2-tailed) si riferisce a un valore p a due code per il test Mann-Whitney, che indica il significato del suo confronto di ranghi per i due gruppi di giocatori. Dal momento che p > .1, la sua conclusione che questi risultati sono insignificanti probabilmente non sta per attirare molto dibattito. BTW, an exact p value is also calculable for these tests, but may take longer with. Mann-Whitney U-test. The Mann-Whitney U-test is a non-parametric method which is used as an alternative to the two-sample Student's t-test.Usually this test is used to compare medians of non-normal distributions X and Y (the t-test is not applicable because X and Y are not normal). The test works correctly under the following conditions Figure 1 - Mann-Whitney Exact Test. We start by filling in the value of zero for U < 0 (columns D through G). We next fill in the values for row 4, namely 1 for U = 0, 1, 2 = n and 0 elsewhere. The values for rows 5 and 6 are similar The Mann-Whitney U test is a non-parametric test used to determine whether two independent groups of data are different. It is a robust test, and is widely used in many social sciences, including quantitative psychology. For more details, have a look at the following post, or refer to an appropriate textbook on the subject