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Nonparametric statistics

Index Nonparametric statistics

Nonparametric statistics is the branch of statistics that is not based solely on parameterized families of probability distributions (common examples of parameters are the mean and variance). [1]

65 relations: Analysis of similarities, Anderson–Darling test, Bootstrapping (statistics), CDF-based nonparametric confidence interval, Cochran's Q test, Cohen's kappa, Data envelopment analysis, Descriptive statistics, Dirichlet process, Edward Arnold (publisher), Edward Wright (mathematician), Friedman test, Histogram, Human sex ratio, Information field theory, Jean D. Gibbons, John Arbuthnot, K-nearest neighbors algorithm, Kaplan–Meier estimator, Kendall rank correlation coefficient, Kendall's W, Kernel (statistics), Kernel density estimation, Kolmogorov–Smirnov test, Kruskal–Wallis one-way analysis of variance, Kuiper's test, Larry A. Wasserman, Latent variable, Level of measurement, Logrank test, Mann–Whitney U test, McNemar's test, Median, Median test, Multivariate analysis, Nonparametric regression, Number, Order statistic, Ordinal data, Parameter, Parametric statistics, Parametrization, Power (statistics), Preference, Probability distribution, Rank product, Ranking, Resampling (statistics), Robust statistics, Semiparametric regression, ..., Siegel–Tukey test, Sign test, Spearman's rank correlation coefficient, Spline (mathematics), Squared ranks test, Statistic, Statistical hypothesis testing, Statistical inference, Statistical model, Statistics, Support vector machine, Tukey–Duckworth test, Wald–Wolfowitz runs test, Wavelet, Wilcoxon signed-rank test. Expand index (15 more) »

Analysis of similarities

Analysis of similarities (ANOSIM) is a non-parametric statistical test widely used in the field of ecology.

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Anderson–Darling test

The Anderson–Darling test is a statistical test of whether a given sample of data is drawn from a given probability distribution.

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Bootstrapping (statistics)

In statistics, bootstrapping is any test or metric that relies on random sampling with replacement.

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CDF-based nonparametric confidence interval

In statistics, cumulative distribution function (CDF)-based nonparametric confidence intervals are a general class of confidence intervals around statistical functionals of a distribution.

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Cochran's Q test

In statistics, in the analysis of two-way randomized block designs where the response variable can take only two possible outcomes (coded as 0 and 1), Cochran's Q test is a non-parametric statistical test to verify whether k treatments have identical effects.

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Cohen's kappa

Cohen's kappa coefficient (κ) is a statistic which measures inter-rater agreement for qualitative (categorical) items.

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Data envelopment analysis

Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers.

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Descriptive statistics

A descriptive statistic (in the count noun sense) is a summary statistic that quantitatively describes or summarizes features of a collection of information, while descriptive statistics in the mass noun sense is the process of using and analyzing those statistics.

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Dirichlet process

In probability theory, Dirichlet processes (after Peter Gustav Lejeune Dirichlet) are a family of stochastic processes whose realizations are probability distributions.

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Edward Arnold (publisher)

Edward Arnold Publishers Ltd was a British publishing house with its head office in London.

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Edward Wright (mathematician)

Edward Wright (baptised 8 October 1561; died November 1615) was an English mathematician and cartographer noted for his book Certaine Errors in Navigation (1599; 2nd ed., 1610), which for the first time explained the mathematical basis of the Mercator projection, and set out a reference table giving the linear scale multiplication factor as a function of latitude, calculated for each minute of arc up to a latitude of 75°.

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Friedman test

The Friedman test is a non-parametric statistical test developed by Milton Friedman.

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A histogram is an accurate representation of the distribution of numerical data.

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Human sex ratio

In anthropology and demography, the human sex ratio is the ratio of males to females in a population.

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Information field theory

Information field theory (IFT) is a Bayesian statistical field theory relating to signal reconstruction, cosmography, and other related areas.

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Jean D. Gibbons

Jean Dickinson Gibbons (née Dickinson, born 1938) is an American statistician, an expert in nonparametric statistics and an author of books on statistics.

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John Arbuthnot

John Arbuthnot (baptised 29 April 1667 – 27 February 1735), often known simply as Dr Arbuthnot, was a Scottish physician, satirist and polymath in London.

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K-nearest neighbors algorithm

In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression.

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Kaplan–Meier estimator

The Kaplan–Meier estimator, also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime data.

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Kendall rank correlation coefficient

In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's tau coefficient (after the Greek letter τ), is a statistic used to measure the ordinal association between two measured quantities.

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Kendall's W

Kendall's W (also known as Kendall's coefficient of concordance) is a non-parametric statistic.

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Kernel (statistics)

The term kernel is a term in statistical analysis used to refer to a window function.

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Kernel density estimation

In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable.

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Kolmogorov–Smirnov test

In statistics, the Kolmogorov–Smirnov test (K–S test or KS test) is a nonparametric test of the equality of continuous, one-dimensional probability distributions that can be used to compare a sample with a reference probability distribution (one-sample K–S test), or to compare two samples (two-sample K–S test).

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Kruskal–Wallis one-way analysis of variance

The Kruskal–Wallis test by ranks, Kruskal–Wallis H test, Laerd Statistics (named after William Kruskal and W. Allen Wallis), or one-way ANOVA on ranks is a non-parametric method for testing whether samples originate from the same distribution.

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Kuiper's test

Kuiper's test is used in statistics to test that whether a given distribution, or family of distributions, is contradicted by evidence from a sample of data.

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Larry A. Wasserman

Larry A. Wasserman is a Canadian statistician and a professor in the Department of Statistics and the Machine Learning Department at Carnegie Mellon University.

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Latent variable

In statistics, latent variables (from Latin: present participle of lateo (“lie hidden”), as opposed to observable variables), are variables that are not directly observed but are rather inferred (through a mathematical model) from other variables that are observed (directly measured).

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Level of measurement

Level of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables.

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Logrank test

In statistics, the logrank test is a hypothesis test to compare the survival distributions of two samples.

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Mann–Whitney U test

In statistics, the Mann–Whitney U test (also called the Mann–Whitney–Wilcoxon (MWW), Wilcoxon rank-sum test, or Wilcoxon–Mann–Whitney test) is a nonparametric test of the null hypothesis that it is equally likely that a randomly selected value from one sample will be less than or greater than a randomly selected value from a second sample.

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McNemar's test

In statistics, McNemar's test is a statistical test used on paired nominal data.

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The median is the value separating the higher half of a data sample, a population, or a probability distribution, from the lower half.

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Median test

In statistics, Mood's median test is a special case of Pearson's chi-squared test.

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Multivariate analysis

Multivariate analysis (MVA) is based on the statistical principle of multivariate statistics, which involves observation and analysis of more than one statistical outcome variable at a time.

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Nonparametric regression

Nonparametric regression is a category of regression analysis in which the predictor does not take a predetermined form but is constructed according to information derived from the data.

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A number is a mathematical object used to count, measure and also label.

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Order statistic

In statistics, the kth order statistic of a statistical sample is equal to its kth-smallest value.

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Ordinal data

Ordinal data is a categorical, statistical data type where the variables have natural, ordered categories and the distances between the categories is not known.

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A parameter (from the Ancient Greek παρά, para: "beside", "subsidiary"; and μέτρον, metron: "measure"), generally, is any characteristic that can help in defining or classifying a particular system (meaning an event, project, object, situation, etc.). That is, a parameter is an element of a system that is useful, or critical, when identifying the system, or when evaluating its performance, status, condition, etc.

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Parametric statistics

Parametric statistics is a branch of statistics which assumes that sample data comes from a population that follows a probability distribution based on a fixed set of parameters.

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Parametrization (or parameterization; also parameterisation, parametrisation) is the process of finding parametric equations of a curve, a surface, or, more generally, a manifold or a variety, defined by an implicit equation.

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Power (statistics)

The power of a binary hypothesis test is the probability that the test correctly rejects the null hypothesis (H0) when a specific alternative hypothesis (H1) is true.

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A preference is a technical term in psychology, economics and philosophy usually used in relation to choosing between alternatives; someone has a preference for A over B if they would choose A rather than B.

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Probability distribution

In probability theory and statistics, a probability distribution is a mathematical function that provides the probabilities of occurrence of different possible outcomes in an experiment.

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Rank product

The rank product is a biologically motivated test for the detection of differentially expressed genes in replicated microarray experiments.

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A ranking is a relationship between a set of items such that, for any two items, the first is either 'ranked higher than', 'ranked lower than' or 'ranked equal to' the second.

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Resampling (statistics)

In statistics, resampling is any of a variety of methods for doing one of the following.

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Robust statistics

Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal.

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Semiparametric regression

In statistics, semiparametric regression includes regression models that combine parametric and nonparametric models.

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Siegel–Tukey test

In statistics, the Siegel–Tukey test, named after Sidney Siegel and John Tukey, is a non-parametric test which may be applied to data measured at least on an ordinal scale.

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Sign test

The sign test is a statistical method to test for consistent differences between pairs of observations, such as the weight of subjects before and after treatment.

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Spearman's rank correlation coefficient

In statistics, Spearman's rank correlation coefficient or Spearman's rho, named after Charles Spearman and often denoted by the Greek letter \rho (rho) or as r_s, is a nonparametric measure of rank correlation (statistical dependence between the rankings of two variables).

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Spline (mathematics)

In mathematics, a spline is a function defined piecewise by polynomials.

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Squared ranks test

In statistics, the Conover squared ranks test is a non-parametric version of the parametric Levene's test for equality of variance.

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A statistic (singular) or sample statistic is a single measure of some attribute of a sample (e.g. its arithmetic mean value).

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Statistical hypothesis testing

A statistical hypothesis, sometimes called confirmatory data analysis, is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables.

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Statistical inference

Statistical inference is the process of using data analysis to deduce properties of an underlying probability distribution.

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Statistical model

A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of some sample data and similar data from a larger population.

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Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.

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Support vector machine

In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.

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Tukey–Duckworth test

In statistics, the Tukey–Duckworth test is a two-sample location test – a statistical test of whether one of two samples was significantly greater than the other.

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Wald–Wolfowitz runs test

The Wald–Wolfowitz runs test (or simply runs test), named after Abraham Wald and Jacob Wolfowitz, both of whom are well known staticians.

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A wavelet is a wave-like oscillation with an amplitude that begins at zero, increases, and then decreases back to zero.

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Wilcoxon signed-rank test

The Wilcoxon signed-rank test is a non-parametric statistical hypothesis test used to compare two related samples, matched samples, or repeated measurements on a single sample to assess whether their population mean ranks differ (i.e. it is a paired difference test).

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[1] https://en.wikipedia.org/wiki/Nonparametric_statistics

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