Linked Questions

4 votes
2 answers

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?
Frank's user avatar
  • 41
0 votes
0 answers

What is the difference between parametric and non-parametric distributions? [duplicate]

I've learnt that for parametrical distributions you can describe the family of statistical model with the parameters, one such example has been the uniform distribution. I just came across a text ...
Tyra's user avatar
  • 11
2 votes
1 answer

What is the drawback of using a non-parametric test when parametric alternative could have been used? [duplicate]

I want to analyze the difference between two paired samples. My initial plan was to compare them using the Wilcoxon test because I didn't want to bother checking whether the data is properly ...
Boris Arkadievich's user avatar
0 votes
0 answers

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 ...
Łukasz Deryło's user avatar
0 votes
0 answers

When it is necessary to assume distribution to calculate probability? [duplicate]

I hope that my question is clear enough to understand. If we need to calculate the probability of an event and we have historical data regarding our parameter of interest - When we have to assume ...
Lex's user avatar
  • 71
102 votes
9 answers

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 ...
Legend's user avatar
  • 4,532
139 votes
8 answers

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 ...
Silverfish's user avatar
  • 23.5k
19 votes
3 answers

Why are parametric tests more powerful than non-parametric tests?

I'd like to understand why parametric tests are more powerful than their non-parametric alternatives. Is the word choice of "power" the same as statistical power? As I understand it, power ...
Nate's user avatar
  • 1,549
18 votes
4 answers

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?
user154510's user avatar
15 votes
3 answers

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 ...
Silverfish's user avatar
  • 23.5k
5 votes
2 answers

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 ...
user avatar
3 votes
3 answers

importance of CLT in t-test and z-test

I was going through the assumptions of z-test and t-test, all most all of the references mention that the data should be normally distributed. There is no mention of estimator's distribution. If the ...
Angadishop's user avatar
6 votes
3 answers

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 ...
Chris's user avatar
  • 171
4 votes
1 answer

t-test when the data population is not normally distributed

I understand that according to CLT the estimator would become normal but, If my population is not normally distributed, let's say it is uniformly distributed. Can I use t-test? let's also assume that ...
Angadishop's user avatar
10 votes
1 answer

Is permutation test superior to t-test in all cases?

All other things being equal is there ever a time when a t-test would be preferable to a permutation test? Computational time may be one reason, but for our purposes assume it does not matter. Isn't ...
WCMC's user avatar
  • 1,058

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