Linked Questions

3
votes
2answers
1k views

Parametric vs nonparametric methods [duplicate]

Are non-parametric methods preferable to parametric methods since the former do not force the model to have a parametric structure?
0
votes
0answers
50 views

Do we need parametric tests? [duplicate]

First of all, sorry for catchy title, my question is not that broad as it suggests. I just came to conclusion that I don't need parametric tests. Instead, I need some feedback if my reasoning makes ...
88
votes
8answers
29k views

If mean is so sensitive, why use it in the first place?

It is a known fact that median is resistant to outliers. If that is the case, when and why would we use the mean in the first place? One thing I can think of perhaps is to understand the presence of ...
97
votes
7answers
79k views

How to choose between t-test or non-parametric test e.g. Wilcoxon in small samples

Certain hypotheses can be tested using Student's t-test (maybe using Welch's correction for unequal variances in the two-sample case), or by a non-parametric test like the Wilcoxon paired signed rank ...
14
votes
4answers
7k views

Are there any non-distance based clustering algorithms?

It seems that for K-means and other related algorithms, clustering is based off calculating distance between points. Is there one that works without it?
13
votes
3answers
3k views

Why is the asymptotic relative efficiency of the Wilcoxon test $3/\pi$ compared to Student's t-test for normally distributed data?

It is well-known that the asymptotic relative efficiency (ARE) of the Wilcoxon signed rank test is $\frac{3}{\pi} \approx 0.955$ compared to Student's t-test, if the data are drawn from a normally ...
4
votes
2answers
4k views

Why does using a non-parametric test decrease power?

I am thinking about using the Mann Whitney U test over Student's classic t-test. But I was warned that I'd lose power and would require a higher sample size to compensate. I don't understand: Why ...
5
votes
3answers
2k views

Effect size for Wilcoxon signed rank test that incorporates the possible range of the attribute

I'm currently working on my master thesis and I'm analysing attributes obtained from digital elevation models (DEMs). I try to compare two point sets for which I extracted altitude values from two DEM ...
1
vote
1answer
105 views

Very small sample compared to comparatively very large baseline

I would like to know if a small test group (~5 samples) is significantly different from baseline (300-400 samples). I initially considered Student's T-Test, but it seems that I wouldn't be able to ...
0
votes
1answer
36 views

Checking the normality of a large sample?

If I want to analyze a large sample size (N = 50.000) of continuous data ($ revenue) from an A/B test, what would then be the best way to check for normality? Thanks in advance!