25
votes
Accepted
Have the reports of the death of the t-test been greatly exaggerated?
I wouldn't say the classic one sample (including paired) and two-sample equal variance t-tests are exactly obsolete, but there's a plethora of alternatives that have excellent properties and in many ...
25
votes
Accepted
Why the p-value of t.test() is not statistically significant when mean values look really different
I agree with @pikachu that the standard deviations are too large
compared with the difference between means for a t test to find
a significant difference.
Thank you for posting your data. It is always ...
24
votes
Accepted
Non-parametric test if two samples are drawn from the same distribution
The Kolmogorov-Smirnov test is the most common way to do this, but there are also some other options.
The tests are based on the empirical cumulative distribution functions. The basic procedure is:
...
16
votes
Accepted
Can I use a Mann-Whitney U Test with a very small sample?
This has been discussed at length on this site. Briefly, the test is valid. But no test is especially helpful because of our inability to interpret large p-values, which do not indicate "no ...
15
votes
Accepted
Why does R say 'cannot compute exact p-values with ties' when I can do it with pen and paper?
The wilcox.test from the standard stats library is limited to cases without ties because it uses an algorithm from the function <...
14
votes
Kolmogorov Smirnov Z vs Mann Whitney U small sample size n= 15?
If the original statement doesn't limit the conditions under which it applies pretty substantially, Field is just wrong on this.
Responding to the quoted section:
In effect, this means it does much ...
14
votes
Detect if there is actually two populations in a sample
There is no way to do this by non-parametric paradigm, just think of it: the sampled distribution is a completely legit one, there is nothing preventing a single-population distribution from having ...
14
votes
Can I use a Mann-Whitney U Test with a very small sample?
Frank's advice is useful; I don't wish my answer to suggest any disagreement with that answer.
The Wilcoxon-Mann-Whitney test "works as it should" in small samples. There's a few things to ...
13
votes
Accepted
When should I use `scipy.stats.wilcoxon` instead of `scipy.stats.ranksums`?
Frank Wilcoxon's 1945 paper [1] described two tests -- for "Unpaired Experiments" and "Paired Comparisons" which have come to be called the (Wilcoxon) rank sum test and the (Wilcoxon) signed rank test ...
13
votes
Accepted
Using wilcox.test() and t.test() in R yielding different p-values
Steady on there!
You have two very small samples there. Statistics is not taught at Hogwarts! No white magic for very small samples.
Not rejecting the null on Shapiro-Wilk doesn't allow the ...
12
votes
What is the interpretation of the p-value of 2.2e-16?
2.2e-16 is the scientific notation of 0.00000000000000022, meaning it is very close to zero. Your statistical software probably uses this notation automatically for very small numbers. You may be able ...
11
votes
Accepted
Why was I told to use a sample size of 30 when using the Mann–Whitney U test?
The Mann Whitney test does not require any specific N.
However, what your instructor is probably talking about is power; that is, with a small N, differences are not going to be statistically ...
11
votes
Why the p-value of t.test() is not statistically significant when mean values look really different
When you consider the difference between means you have to use a different unit than the simple absolute difference. Take into account that you are measuring the difference in means produced by two ...
11
votes
Accepted
What can cause exploding statistic values and p-values near zero with the Wilcoxon-Mann-Whitney test?
Nothing out of the ordinary is going on from the sound of it.
In almost all cases, I get huge values for the statistic
Have you looked at the range of possible values for the statistic?
For the ...
10
votes
Accepted
Rank and z-transform instead of Wilcoxon?
(Pulls Conover [1] off the bookshelf...)
This idea is quite old; it dates back at least to van der Waerden (1952/1953) [2][3], who suggested a test that corresponds to the Kruskal Wallis but with ...
10
votes
Accepted
Relationship between AUC and U Mann-Whitney statistic
Ok, I found the answer and as I expected it is trivial. $U$ test statistic value depends on the group it is calculated for (it does not affect the test result in anyway). In the code I wrote the test ...
10
votes
Mann-Whitney U Test Definition of U
Anyone is allowed to give any possible name for the test statistic they design. Mann and Whitney (1947) decided to name the one they proposed as "$U$". In their paper they do not give any reasons why ...

Tim♦
- 134k
10
votes
Accepted
Interpretation of p-value in Mann-Whitney rank test
The p-value represents the probability of getting a test-statistic at least as extreme$^\dagger$ as the one you had in your sample, if the null hypothesis were true.
A high p-value indicates you saw ...
10
votes
Accepted
Mann-Whitney-Wilcoxon Test on highly unbalanced groups.
In no way will the difference in sample sizes adversely affect the Mann-Whitney-Wilcoxon test. It's explicitly suitable for groups of different sizes, and how different doesn't impact the essential ...
10
votes
Accepted
Always use Welch-t test (unequal variances t-test) instead of Student-t or Mann-Whitney test?
There have been a number of papers which examine this issue. Most of them come to the conclusion that Welch's version of the t-test can be safely used in most circumstances.
The only situation in ...
10
votes
Is the Wilcoxon rank-sum test a nonparametric alternative to the two sample t-test? Null hypotheses are different
Is the Wilcoxon rank-sum test a nonparametric alternative to the two sample t-test?
Yes and no. (Go not to the elves for counsel...)
Speaking broadly, any given test statistic has some power curve ...
10
votes
Accepted
Detect if there is actually two populations in a sample
Let's start with terminology. Population in statistics is the "set of entities under study". When designing the study, we define the population of interest and then draw samples from this population. ...

Tim♦
- 134k
10
votes
Accepted
What does comparing mean rank mean?
When comparing two independent samples, you want to rank all the data together.
Revising your example:
Sample A
...
10
votes
Accepted
Should I make equally sized samples for the Mann-Whitney U test if originally I have unequal sample sizes
Use your original data.
Claims about losing power when groups have unequal sizes make more sense in the context of designing the experiment. If you have enough resources to make $100$ observations, ...
9
votes
Where does the number 12 come from and why is it the same 12 in Wilcoxon and Kruskal Wallis?
In both cases 12 appears when approximating the distribution of the test statistic with a normal and chi-square respectively because the statistic must first be written in a standardized form (if you ...
9
votes
Can the Wilcoxon rank sum test give a different result to the Kolmogorov-Smirnov test result?
Statistical tests measure differences between samples in different ways and are sensitive to different aspects of the distributional differences.
It's certainly possible for one test to reject and ...
9
votes
Detect if there is actually two populations in a sample
In statistical terms, you are wondering whether your data comes from a mixture of two (or more) populations, as against coming from a single population. Looking at the mixture or more specifically the ...
9
votes
How to tune `wilcox.test` in `R` to compare means instead of medians
In spite of what the linked page says (and it clearly does at the time of writing*), the Wilcoxon-Mann-Whitney test does not compare medians. If you're looking at pure-shift alternatives, it's ...
8
votes
Accepted
Different ways of performing the Wilcoxon rank sum test and the interpretation of the resulting W-statistic
The Mann-Whitney U statistic counts 1 every time an observation in one sample is less than an observation in the other sample, across all cross-sample pairs of observations. However, it's arbitrary ...
8
votes
How can I find the expected value and variance of the Wilcoxon Sum of Ranks test?
Let $F$ be the distribution of the sample $\mathbf{X}=(X_{1},...,X_{n1})$ and $G$ be the distribution of the sample $\mathbf{Y}=(Y_{1},...,Y_{n2})$. Furthermore, assume that both $F$ and $G$ are ...
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