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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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 ...
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Kendall Tau or Spearman's rho?
In which cases should one prefer the one over the other?
I found someone who claims an advantage for Kendall, for pedagogical reasons, are there other reasons?
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What exactly does a non-parametric test accomplish & What do you do with the results?
I have a feeling this may have been asked elsewhere, but not really with the type of basic description I need. I know non-parametric relies on the median instead of the mean to compare... something. ...
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Why would parametric statistics ever be preferred over nonparametric?
Can someone explain to me why would anyone choose a parametric over a nonparametric statistical method for hypothesis testing or regression analysis?
In my mind, it's like going for rafting and ...
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What is the non-parametric equivalent of a two-way ANOVA that can include interactions?
Hi I am trying to find the non-parametric equivalent of a two-way ANOVA (3x4 design) which is capable of including interactions. From my reading in Zar 1984 "Biostatistical analysis" this is possible ...
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Which permutation test implementation in R to use instead of t-tests (paired and non-paired)?
I have data from an experiment that I analyzed using t-tests. The dependent variable is interval scaled and the data are either unpaired (i.e., 2 groups) or paired (i.e., within-subjects).
E.g. (...
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Is there an equivalent to Kruskal Wallis one-way test for a two-way model?
If the model does not satisfy ANOVA assumptions (normality in particular), if one-way, Kruskal-Wallis non-parametric test is recommended. But, what if you have multiple factors?
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Determine if a heavy tailed distributed process has improved significantly
I observe processing times of a process before and after a change in order to find out, if the process has improved by the change. The process has improved, if the processing time is reduced.
The ...
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Bootstrap vs. permutation hypothesis testing
There are several popular resampling techniques, which are often used in practice, such as bootstrapping, permutation test, jackknife, etc. There are numerous articles & books discuss these ...
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Should I use t-test on highly skewed and discrete data?
I have samples from a highly skewed dataset about users' participation (e.g.: number of posts), that have different sizes (but not less than 200) and I want to compare their mean. For that, I'm using ...
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Is there a reliable nonparametric confidence interval for the mean of a skewed distribution?
Very skewed distributions such as the log-normal do not result in accurate bootstrap confidence intervals. Here is an example showing that the left and right tail areas are far from the ideal 0.025 ...
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Why is the Mann–Whitney U test significant when the medians are equal?
I've received a results from a Mann-Whitney rank test that I don't understand.
The median of the 2 populations is identical (6.9). The uppper and lower quantiles of each population are:
6.64 & 7....
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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 ...
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Non-parametric measure of strength of association between an ordinal and a continuous random variable
I'm throwing here the problem as I received it.
I have two random variables. One of which is continuous (Y) and the other one which is discrete and will be approached as ordinal (X). I put below the ...
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Relative efficiency of Wilcoxon signed rank in small samples
I have seen in published literature (and posted on here) that the asymptotic relative efficiency of the Wilcoxon signed rank test is at least 0.864 when compared to the t test. I have also heard that ...
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What exactly is the difference between a parametric and non-parametric model?
I am confused with the definition of non-parametric model after reading this link Parametric vs Nonparametric Models and Answer comments of my another question.
Originally I thought "parametric vs ...
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When to check model assumptions
Statistical methods are based on model assumptions. For example, an independent one-way ANOVA makes the following assumptions:
Normally distributed residuals
Homogeneity of variance
Independence of ...
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Applicability of chi-square test if many cells have frequencies less than 5
To find association between peer's support (independent variable) and work satisfaction (dependent variable) I wish to apply chi-square test. Peer's support is categories in four groups according to ...
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Which statistical analysis should I perform if the data sets are not normally distributed?
I am doing an experiment where there are two independent groups; one is the group of "infected" patients another is the group of "sepsis" patients. I am comparing "platelet monocyte aggregates(PMA)" ...
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A non-parametric repeated-measures multi-way Anova in R?
The following question is one of those holy grails for me for some time now, I hope someone might be able to offer a good advice.
I wish to perform a non-parametric repeated measures multiway anova ...
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Why are Gaussian process models called non-parametric?
I am a bit confused. Why are Gaussian processes called non parametric models?
They do assume that the functional values, or a subset of them, have a Gaussian prior with mean 0 and covariance function ...
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Should I use t-test on highly skewed data ? Scientific proof, please?
I have samples from a highly skewed (looking like an exponential distribution) dataset about users' participation (e.g.: number of posts), that have different sizes (but not less than 200) and I want ...
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Checking ANOVA assumptions
A few months ago I posted a question about homoscedasticity tests in R on SO, and Ian Fellows answered that (I'll paraphrase his answer very loosely):
Homoscedasticity tests are not a good tool ...
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Why are all the permutations of i.i.d. samples from a continuous distribution equally likely?
Suppose $X$ is i.i.d from a continuous distribution
Why is$$P(X_{i_1}<X_{i_2}<\cdots<X_{i_3})=P(X_{j_1}<X_{j_2}<\cdots<X_{j_3})=\frac{1}{n!}$$for all $i,j$?
I think we can reason ...
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Wilcoxon Signed Rank Symmetry Assumption
The assumption of symmetricity for signed rank test (and its relevance) is becoming extremely confusing for me. I am hypothesizing that sub-population A (before treatment) and sub-population B (after ...
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Plotting non-parametric (E)CDF confidence envelopes for comparison
I have previously asked about a way to test whether two samples are drawn from the same distribution (Non-parametric test if two samples are drawn from the same distribution). I was very glad to learn ...
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Power analysis for Kruskal-Wallis or Mann-Whitney U test using R?
Is it possible to perform a power analysis for the Kruskal-Wallis and Mann-Whitney U test? If yes, are there any R packages/functions that perform it?
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Is there any statistical test that is parametric and non-parametric?
Is there any statistical test that is parametric and non-parametric?
This question was asked by an interview panel. Is it valid question?
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Is there a multiple-sample version or alternative to the Kolmogorov-Smirnov Test?
I am comparing the size distribution of trees in six pairs of plots where one plot received a treatment and the other a control. Using a Kolmogorov-Smirnov test on each pair of plots I find that $p$ ...
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What is "Targeted Maximum Likelihood Expectation"?
I'm trying to understand some papers by Mark van der Laan. He's a theoretical statistician at Berkeley working on problems overlap significantly with machine learning. One problem for me (besides ...
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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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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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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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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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Is the inference from a parametric test valid when the population distribution is not normal?
This question arose from reading this post: T-test for non normal when N>50?
In the response to this post, the author outlines really well that the assumption of normality with regard to the t-...
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bootstrapping a linear mixed model with R's lmeresampler or lme4 or a robust regression?
considering that I have a very small sample and that my residuals are non-normally distributed, I've decided to perform a lmer() with bootstrapping. This is my very ...
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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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How to compare two non-normally distributed samples with very different sizes? (Mann-Whitney vs Randomization/Bootstrap)
Perhaps this is a very basic question, but I didn't find yet a simple solution for this simple problem:
I want to compare two samples (say X and Y) for a continuous variable which is non-normally ...
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Mann Whitney Test: Clearing Up Confusion
I have been reading many statistical websites stating that the Mann Whitney test is a test of medians. However, I believe that this is not really true? It is a test of the difference in the ranks. The ...
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Difference of 'centers' of 2 non-normal samples with Mann-Whitney test
I have 2 non-normally distributed samples of different sizes (N1~=N2).
To evaluate whether there is a significant difference between these samples, I used the Mann Whitney U test (...
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