Questions tagged [nonparametric]
Use this tag to ask about the nature of nonparametric or parametric methods, or the difference between the two. Nonparametric methods generally rely on few assumptions about the underlying distributions, whereas parametric methods make assumptions that allow data to be described by a small number of parameters.
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Is there an alternative to the Kolmogorov-Smirnov test for tied data with correction?
I've got a bunch of data from two samples (control and treated), each containing several thousand values which are to undergo significance testing in R. Theoretically, the values should be continuous, ...
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Friedman test vs Wilcoxon test
I'm trying to assess performance of a supervised machine learning classification algorithm. The observations fall into nominal classes (2 for the time being, however I'd like to generalize this to ...
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Permutation test in R
I have the following data for 10 subjects based on before and after measurements:
...
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Nonparametric equivalent of ANCOVA for continuous dependent variables
I have an independent categorical variable ($X$ with two categories, $x_{1}$ and $x_{2}$) and two continuous dependent variables ($y$ and $z$).
Using a Mann Whitney test, I know that $y$ is ...
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Estimate population quantiles from subpopulations' quantiles
Suppose there is a population partitioned arbitrarily into a set of subpopulations that completely cover the original population. Assume that for some variable, we know each subpopulation's quintiles ...
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Is there a non-parametric form of a 3-way ANOVA?
I am currently in the process of writing a publication about the home range of cat shark species in South Africa. However, I am currently struggling with how to create an interaction model of shark ...
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Is there an assumption-free ANOVA?
ANOVA presupposes a normal distribution and equal variance. Kruskal–Wallis (non-parametric ANOVA) assumes that all population distributions are the same (except their parameters).
I'd like to know if ...
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What is the weak side of decision trees?
Decision trees seems to be a very understandable machine learning method.
Once created it can be easily inspected by a human which is a great advantage in some applications.
What are the practical ...
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Non-parametric test if two samples are drawn from the same distribution
I would like to test the hypothesis that two samples are drawn from the same population, without making any assumptions about the distributions of the samples or the population. How should I do this?
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How to run two-way ANOVA on data with neither normality nor equality of variance in R?
I am working on my master thesis at the moment and planned on running the statistics with SigmaPlot. However, after spending some time with my data I came to the conclusion that SigmaPlot might not be ...
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Statistical test for two distributions where only 5-number summary is known?
I have two distributions where only the 5-number summary (minimum, 1st quartile, median, 3rd quartile, maximum) and sample size are known. Contrary to the question here, not all data points are ...
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Propensity score matching vs non-parametric regression
I am trying to understand the benefit of propensity matching over non-parametric regression for causal inference from non-experimental data.
As background: the way I understand it, parametric ...
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Is ordinal or interval data required for the Wilcoxon signed rank test?
Having looked at multiple online sources, I can't seem to get a straight answer. Could someone please clarify for me if ordinal data is sufficient to use for the WSRT and if not, is the sign test an ...
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What inferential method produces the empirical CDF?
The empirical cdf is an estimate of the cdf. What kind of estimation method (such as method of moments, MLE, ...) constructs the empirical cdf?
Is the empirical cdf a nonparametric estimate? Do ...
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Jonckheere-Terpstra interpretation
I am running the Jonckheere-Terpstra in place of Kruskal-Wallis test, as my factor is in ordinal scale (i.e. groups can be ordered).
The Asymptotic significance (2-tailed) is 0.000, so it seems there ...
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