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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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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Is the Friedman Test Suitable For an Analysis of Pre/Post-Intervention Choices From Survey Data?
We sent out a survey to find if educational material about a type of surgery would potentially influence the decision of subjects. Prior to giving them this educational material we asked them ...
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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 ...
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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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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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Welch ANOVA for Comparisons of Elevation & altered Sediment Accretion of Sea Ecosystems: Large DEM with no normal distribution & heterogeneity
I am investigating the elevation characteristics and sediment accretion effects of two distinct ecosystems within the Wadden Sea, impacted by the bioinvasion of one species (ecosystem one) and ...
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Non parametric tests for 2 way anova and linear model? [duplicate]
My dissertation is due very soon and I have only just realised a large mistake in my work. I misread the normality test I used, which actually showed non normal data- but I still have homogeneity of ...
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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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In what ways is Gaussian Process Regression both parametric and non-parametric?
Gaussian Process Regression is considered a "non-parametric" model. However, the term "non-parametric" is often used imprecisely to mean different things, leading to questions ...
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Singular Spectrum Analysis Decomposition on single input signal using PyTS module
I read this paper and was curious to apply it on a single-channel audio recording of mixed sources. It is about Singular Spectrum Analysis (SSA).
The paper mentions that a key component of the ...
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Estimating Confidence in Feature Rankings from Multiple Experiments with Non-Normal Data
Hello dear Cross Validated Community,
I am a new doctoral student in bioinformatics, and I am working on a project involving multiple experiments, each generating a single numerical result for each of ...
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Non-Parametric Regression with an Omitted Variable
Suppose we use the Kernel Regression Estimator $$\hat{m}(c)=\frac{\sum_{i=1}^n K\left(\frac{x_i-c}{h}\right)y_i}{\sum_{i=1}^n K\left(\frac{x_i-c}{h}\right)}$$
where $h\to 0$ and $nh\to \infty$ as $n\...
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Fitting an functional autoregressive model in R with mgcv
I'm working with the 'mgcv' package in R and I just want to know if I am going about the right way of fitting a functional autoregressive (FAR) model. The FAR model is represented as
$$Y=f_1(x.1)x.1+...
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Non-normal distribution and heterogenous variances
I have a data set in which I measured a continuous variable (positive, continuous data) in response to different treatments(15 different pathogens) and I am unsure how to statistically analyse the ...
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Equivalent to Spearman correlation for non-monotonic data
I have several datasets of independent variables that have a monotonic (but non-linear) relationship. If I want to assess if they're correlated, the test of choice is Spearman's (rho) or Kendall's (...
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