0–9

* 1.96 * 2SLS (two-stage least squares) redirects to

instrumental variable In statistics, econometrics, epidemiology and related disciplines, the method of instrumental variables (IV) is used to estimate causal relationships when controlled experiments are not feasible or when a treatment is not successfully delivered t ...

*3SLS – see three-stage least squares * 68–95–99.7 rule *

100-year flood A 100-year flood is a flood event that has a 1 in 100 chance (1% probability) of being equaled or exceeded in any given year. The 100-year flood is also referred to as the 1% flood, since its annual exceedance probability is 1%.Holmes, R.R., Jr. ...

A

A priori probability An ''a priori'' probability is a probability that is derived purely by deductive reasoning. One way of deriving ''a priori'' probabilities is the principle of indifference, which has the character of saying that, if there are ''N'' mutually exclu ...

* Abductive reasoning *

Absolute deviation In mathematics and statistics, deviation is a measure of difference between the observed value of a variable and some other value, often that variable's mean. The sign of the deviation reports the direction of that difference (the deviation is posi ...

* Absolute risk reduction *

Absorbing Markov chain In the mathematical theory of probability, an absorbing Markov chain is a Markov chain in which every state can reach an absorbing state. An absorbing state is a state that, once entered, cannot be left. Like general Markov chains, there can be c ...

ABX test An ABX test is a method of comparing two choices of sensory stimuli to identify detectable differences between them. A subject is presented with two known samples (sample , the first reference, and sample , the second reference) followed by one unkn ...

Accelerated failure time model In the statistics, statistical area of survival analysis, an accelerated failure time model (AFT model) is a parametric statistics, parametric model that provides an alternative to the commonly used proportional hazards models. Whereas a proportio ...

Acceptable quality limit The acceptable quality limit (AQL) is the worst tolerable process ''average'' (''mean'') in percentage or ratio that is still considered acceptable; that is, it is at an acceptable quality level.Dodge, Y. (2003) ''The Oxford Dictionary of Statisti ...

* Acceptance sampling *

Accidental sampling Convenience sampling (also known as grab sampling, accidental sampling, or opportunity sampling) is a type of non-probability sampling that involves the sample being drawn from that part of the population that is close to hand. This type of sampl ...

* Accuracy and precision * Accuracy paradox * Acquiescence bias * Actuarial science *

Adapted process In the study of stochastic processes, an adapted process (also referred to as a non-anticipating or non-anticipative process) is one that cannot "see into the future". An informal interpretation is that ''X'' is adapted if and only if, for every re ...

Adaptive estimator In statistics, an adaptive estimator is an estimator in a parametric or semiparametric model with nuisance parameters such that the presence of these nuisance parameters does not affect efficiency of estimation. Definition Formally, let paramet ...

* Additive Markov chain * Additive model *

Additive smoothing In statistics, additive smoothing, also called Laplace smoothing or Lidstone smoothing, is a technique used to smooth categorical data. Given a set of observation counts \textstyle from a \textstyle -dimensional multinomial distribution with ...

* Additive white Gaussian noise *Adjusted Rand index – see

Rand index The RAND Corporation (from the phrase "research and development") is an American nonprofit global policy think tank created in 1948 by Douglas Aircraft Company to offer research and analysis to the United States Armed Forces. It is financed ...

(subsection) *

ADMB ADMB or AD Model Builder is a free and open source software suite for non-linear statistical modeling. It was created by David Fournier and now being developed by the ADMB Project, a creation of the non-profit ADMB Foundation. The "AD" in AD Model ...

software * Admissible decision rule *

Age adjustment In epidemiology and demography, age adjustment, also called age standardization, is a technique used to allow statistical populations to be compared when the age profiles of the populations are quite different. Example For example, in 2004/5, two ...

* Age-standardized mortality rate * Age stratification *

Aggregate data Aggregate data is high-level data which is acquired by combining individual-level data. For instance, the output of an industry is an aggregate of the firms’ individual outputs within that industry. Aggregate data are applied in statistics, d ...

* Aggregate pattern *

Akaike information criterion The Akaike information criterion (AIC) is an estimator of prediction error and thereby relative quality of statistical models for a given set of data. Given a collection of models for the data, AIC estimates the quality of each model, relative to e ...

Algebra of random variables The algebra of random variables in statistics, provides rules for the symbolic manipulation of random variables, while avoiding delving too deeply into the mathematically sophisticated ideas of probability theory. Its symbolism allows the treat ...

* Algebraic statistics *

Algorithmic inference Algorithmic inference gathers new developments in the statistical inference methods made feasible by the powerful computing devices widely available to any data analyst. Cornerstones in this field are computational learning theory, granular computi ...

Algorithms for calculating variance Algorithms for calculating variance play a major role in computational statistics. A key difficulty in the design of good algorithms for this problem is that formulas for the variance may involve sums of squares, which can lead to numerical instab ...

All models are wrong All or ALL may refer to: Language * All, an indefinite pronoun in English * All, one of the English determiners * Allar language (ISO 639-3 code) * Allative case (abbreviated ALL) Music * All (band), an American punk rock band * ''All'' (All ...

* All-pairs testing *

Allan variance The Allan variance (AVAR), also known as two-sample variance, is a measure of frequency stability in clocks, oscillators and amplifiers. It is named after David W. Allan and expressed mathematically as \sigma_y^2(\tau). The Allan deviation (ADE ...

Alignments of random points Alignments of random points in a plane can be demonstrated by statistics to be counter-intuitively easy to find when a large number of random points are marked on a bounded flat surface. This has been put forward as a demonstration that ley lin ...

Almost surely In probability theory, an event is said to happen almost surely (sometimes abbreviated as a.s.) if it happens with probability 1 (or Lebesgue measure 1). In other words, the set of possible exceptions may be non-empty, but it has probability 0 ...

Alpha beta filter An alpha beta filter (also called alpha-beta filter, f-g filter or g-h filterEli Brookner: Tracking and Kalman Filtering Made Easy. Wiley-Interscience, 1st edition, 4 1998.) is a simplified form of observer for estimation, data smoothing and contro ...

* Alternative hypothesis * Analyse-it – software * Analysis of categorical data *

Analysis of covariance Analysis of covariance (ANCOVA) is a general linear model which blends ANOVA and regression. ANCOVA evaluates whether the means of a dependent variable (DV) are equal across levels of a categorical independent variable (IV) often called a tre ...

Analysis of molecular variance Analysis of molecular variance (AMOVA), is a statistical model for the molecular algorithm in a single species, typically biology, biological. The name and model are inspired by ANOVA. The method was developed by Laurent Excoffier, Peter Smouse and ...

* Analysis of rhythmic variance *

Analysis of variance Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician ...

* Analytic and enumerative statistical studies *

Ancestral graph In statistics and Markov modeling, an ancestral graph is a type of mixed graph to provide a graphical representation for the result of marginalizing one or more vertices in a graphical model that takes the form of a directed acyclic graph In mat ...

Anchor test In psychometrics, an anchor test is a common set of test items administered in combination with two or more alternative forms of the test with the aim of establishing the equivalence of the test scores on the alternative forms. The purpose of the a ...

Ancillary statistic An ancillary statistic is a measure of a sample whose distribution (or whose pmf or pdf) does not depend on the parameters of the model. An ancillary statistic is a pivotal quantity that is also a statistic. Ancillary statistics can be used to c ...

ANCOVA Analysis of covariance (ANCOVA) is a general linear model which blends ANOVA and regression. ANCOVA evaluates whether the means of a dependent variable (DV) are equal across levels of a categorical independent variable (IV) often called a tre ...

redirects to

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. In its basic form, the test assumes that there are no parameters to be estimated in the distribution being tested, ...

ANOVA Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician ...

ANOVA on ranks In statistics, one purpose for the analysis of variance (ANOVA) is to analyze differences in means between groups. The test statistic, ''F'', assumes independence of observations, homogeneous variances, and population normality. ANOVA on ranks is ...

* ANOVA–simultaneous component analysis *

Anomaly detection In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority o ...

* Anomaly time series * Anscombe transform * Anscombe's quartet * Antecedent variable *

Antithetic variates In statistics, the antithetic variates method is a variance reduction technique used in Monte Carlo methods. Considering that the error in the simulated signal (using Monte Carlo methods) has a one-over square root convergence, a very large number ...

Approximate Bayesian computation Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics that can be used to estimate the posterior distributions of model parameters. In all model-based statistical inference, the like ...

Approximate entropy In statistics, an approximate entropy (ApEn) is a technique used to quantify the amount of regularity and the unpredictability of fluctuations over time-series data. For example, consider two series of data: : Series A: (0, 1, 0, 1, 0, 1, 0, 1, 0, ...

* Arcsine distribution *

Area chart An area chart or area graph displays graphically quantitative data. It is based on the line chart. The area between axis and line are commonly emphasized with colors, textures and hatchings. Commonly one compares two or more quantities with an ar ...

* Area compatibility factor *

ARGUS distribution In physics, the ARGUS distribution, named after the particle physics experiment ARGUS, is the probability distribution of the reconstructed invariant mass of a decayed particle candidate in continuum background. Definition The probability dens ...

* Arithmetic mean *

Armitage–Doll multistage model of carcinogenesis The Armitage–Doll model is a statistical model of carcinogenesis, proposed in 1954 by Peter Armitage and Richard Doll, in which a series of discrete mutations result in cancer.Armitage, P. and Doll, R. (1954"The Age Distribution of Cancer and a M ...

* Arrival theorem *

Artificial neural network Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected unit ...

Ascertainment bias In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample of a population (or non-human f ...

* ASReml software *

Association (statistics) In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. Although in the broadest sense, "correlation" may indicate any type of association, in statistics ...

Association mapping In genetics, association mapping, also known as " linkage disequilibrium mapping", is a method of mapping quantitative trait loci (QTLs) that takes advantage of historic linkage disequilibrium to link phenotypes (observable characteristics) to geno ...

* Association scheme *

Assumed mean In statistics the assumed mean is a method for calculating the arithmetic mean and standard deviation of a data set. It simplifies calculating accurate values by hand. Its interest today is chiefly historical but it can be used to quickly estimate t ...

Astrostatistics Astrostatistics is a discipline which spans astrophysics, statistical analysis and data mining. It is used to process the vast amount of data produced by automated scanning of the cosmos, to characterize complex datasets, and to link astronomical d ...

Asymptotic distribution In mathematics and statistics, an asymptotic distribution is a probability distribution that is in a sense the "limiting" distribution of a sequence of distributions. One of the main uses of the idea of an asymptotic distribution is in providing ...

Asymptotic equipartition property In information theory, the asymptotic equipartition property (AEP) is a general property of the output samples of a stochastic source. It is fundamental to the concept of typical set used in theories of data compression. Roughly speaking, the th ...

(information theory) *

Asymptotic normality In mathematics and statistics, an asymptotic distribution is a probability distribution that is in a sense the "limiting" distribution of a sequence of distributions. One of the main uses of the idea of an asymptotic distribution is in providing ap ...

redirects to

Asymptotic relative efficiency In statistics, efficiency is a measure of quality of an estimator, of an experimental design, or of a hypothesis testing procedure. Essentially, a more efficient estimator, needs fewer input data or observations than a less efficient one to achi ...

redirects to

Efficiency (statistics) In statistics, efficiency is a measure of quality of an estimator, of an experimental design, or of a hypothesis testing procedure. Essentially, a more efficient estimator, needs fewer input data or observations than a less efficient one to ach ...

Asymptotic theory (statistics) In statistics, asymptotic theory, or large sample theory, is a framework for assessing properties of estimators and statistical tests. Within this framework, it is often assumed that the sample size may grow indefinitely; the properties of estimato ...

* Atkinson index *

Attack rate In epidemiology, the attack rate is the proportion of an at-risk population that contracts the disease during a specified time interval. It is used in hypothetical predictions and during actual outbreaks of disease. An at-risk population is defined ...

* Augmented Dickey–Fuller test *

Aumann's agreement theorem Aumann's agreement theorem was stated and proved by Robert Aumann in a paper titled "Agreeing to Disagree", which introduced the set theoretic description of common knowledge. The theorem concerns agents who share a common prior and update their ...

* Autocorrelation ** Autocorrelation plot redirects to

Correlogram In the analysis of data, a correlogram is a chart of correlation statistics. For example, in time series analysis, a plot of the sample autocorrelations r_h\, versus h\, (the time lags) is an autocorrelogram. If cross-correlation is plo ...

Autocovariance In probability theory and statistics, given a stochastic process, the autocovariance is a function that gives the covariance of the process with itself at pairs of time points. Autocovariance is closely related to the autocorrelation of the process ...

* Autoregressive conditional duration *

Autoregressive conditional heteroskedasticity In econometrics, the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance of the current error term or innovation as a function of the actual sizes of the previous ti ...

Autoregressive fractionally integrated moving average In statistics, autoregressive fractionally integrated moving average models are time series models that generalize ARIMA (''autoregressive integrated moving average'') models by allowing non-integer values of the differencing parameter. These model ...

Autoregressive integrated moving average In statistics and econometrics, and in particular in time series analysis, an autoregressive integrated moving average (ARIMA) model is a generalization of an autoregressive moving average (ARMA) model. Both of these models are fitted to time ser ...

Autoregressive model In statistics, econometrics and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it is used to describe certain time-varying processes in nature, economics, etc. The autoregressive model spe ...

Autoregressive–moving-average model In the statistical analysis of time series, autoregressive–moving-average (ARMA) models provide a parsimonious description of a (weakly) stationary stochastic process in terms of two polynomials, one for the autoregression (AR) and the second ...

* Auxiliary particle filter *

Average In ordinary language, an average is a single number taken as representative of a list of numbers, usually the sum of the numbers divided by how many numbers are in the list (the arithmetic mean). For example, the average of the numbers 2, 3, 4, 7 ...

Average treatment effect The average treatment effect (ATE) is a measure used to compare treatments (or interventions) in randomized experiments, evaluation of policy interventions, and medical trials. The ATE measures the difference in mean (average) outcomes between units ...

Averaged one-dependence estimators Averaged one-dependence estimators (AODE) is a probabilistic classification learning technique. It was developed to address the attribute-independence problem of the popular naive Bayes classifier. It frequently develops substantially more accur ...

Azuma's inequality In probability theory, the Azuma–Hoeffding inequality (named after Kazuoki Azuma and Wassily Hoeffding) gives a concentration result for the values of martingales that have bounded differences. Suppose \ is a martingale (or super-martingale ...

B

BA model BA, Ba, or ba may refer to: Businesses and organizations * Bangladesh Army * Bibliotheca Alexandrina, an Egyptian library and cultural center * Boeing (NYSE stock symbol BA) * Booksellers Association of the UK and Ireland * Boston Acoustics, ...

model for a random network *

Backfitting algorithm In statistics, the backfitting algorithm is a simple iterative procedure used to fit a generalized additive model. It was introduced in 1985 by Leo Breiman and Jerome Friedman along with generalized additive models. In most cases, the backfitting ...

* Balance equation * Balanced incomplete block design redirects to Block design *

Balanced repeated replication Balanced repeated replication is a statistical technique for estimating the sampling variability of a statistic obtained by stratified sampling. Outline of the technique # ''Select balanced half-samples'' from the full sample. # ''Calculate t ...

* Balding–Nichols model *

Banburismus Banburismus was a cryptanalytic process developed by Alan Turing at Bletchley Park in Britain during the Second World War. It was used by Bletchley Park's Hut 8 to help break German ''Kriegsmarine'' (naval) messages enciphered on Enigma machin ...

related to Bayesian networks *

Bangdiwala's B Bangdiwala's B statistic was created by Shrikant Bangdiwala in 1985 and is a measure of inter-rater agreement.Bangwidala S (1985) A graphical test for observer agreement. Proc 45th Int Stats Institute Meeting, Amsterdam, 1, 307–308Bangdiwala K ...

* Bapat–Beg theorem *

Bar chart A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent. The bars can be plotted vertically or horizontally. A vertical bar chart i ...

Barabási–Albert model The Barabási–Albert (BA) model is an algorithm for generating random scale-free networks using a preferential attachment mechanism. Several natural and human-made systems, including the Internet, the World Wide Web, citation networks, and s ...

* Barber–Johnson diagram *

Barnard's test In statistics, Barnard’s test is an exact test used in the analysis of contingency tables with one margin fixed. Barnard’s tests are really a class of hypothesis tests, also known as unconditional exact tests for two independent binomials. ...

* Barnardisation * Barnes interpolation * Bartlett's method *

Bartlett's test In statistics, Bartlett's test, named after Maurice Stevenson Bartlett, is used to test homoscedasticity, that is, if multiple samples are from populations with equal variances. Some statistical tests, such as the analysis of variance, assume tha ...

* Bartlett's theorem *

Base rate In probability and statistics, the base rate (also known as prior probabilities) is the class of probabilities unconditional on "featural evidence" (likelihoods). For example, if 1% of the population were medical professionals, and remaining ...

Baseball statistics Baseball statistics play an important role in evaluating the progress of a player or team. Since the flow of a baseball game has natural breaks to it, and normally players act individually rather than performing in clusters, the sport lends itsel ...

* Basu's theorem *

Bates distribution In probability and business statistics, the Bates distribution, named after Grace Bates, is a probability distribution of the mean of a number of statistically independent uniformly distributed random variables on the unit interval. This dist ...

Baum–Welch algorithm In electrical engineering, statistical computing and bioinformatics, the Baum–Welch algorithm is a special case of the expectation–maximization algorithm used to find the unknown parameters of a hidden Markov model (HMM). It makes use of the ...

* Bayes classifier *

Bayes error rate In statistical classification, Bayes error rate is the lowest possible error rate for any classifier of a random outcome (into, for example, one of two categories) and is analogous to the irreducible error.K. Tumer, K. (1996) "Estimating the Bayes e ...

* Bayes estimator *

Bayes factor The Bayes factor is a ratio of two competing statistical models represented by their marginal likelihood, and is used to quantify the support for one model over the other. The models in questions can have a common set of parameters, such as a nul ...

Bayes linear statistics Bayes linear statistics is a subjectivist statistical methodology and framework. Traditional subjective Bayesian analysis is based upon fully specified probability distributions, which are very difficult to specify at the necessary level of detail ...

Bayes' rule In probability theory and statistics, Bayes' theorem (alternatively Bayes' law or Bayes' rule), named after Thomas Bayes, describes the probability of an event, based on prior knowledge of conditions that might be related to the event. For examp ...

* Bayes' theorem **

Evidence under Bayes theorem The use of evidence under Bayes' theorem relates to the probability of finding evidence in relation to the accused, where Bayes' theorem concerns the probability of an event and its inverse. Specifically, it compares the probability of finding p ...

Bayesian Thomas Bayes (/beɪz/; c. 1701 – 1761) was an English statistician, philosopher, and Presbyterian minister. Bayesian () refers either to a range of concepts and approaches that relate to statistical methods based on Bayes' theorem, or a followe ...

– disambiguation * Bayesian average * Bayesian brain *

Bayesian econometrics Bayesian econometrics is a branch of econometrics which applies Bayesian principles to economic modelling. Bayesianism is based on a degree-of-belief interpretation of probability, as opposed to a relative-frequency interpretation. The Bayesian ...

* Bayesian experimental design *

Bayesian game In game theory, a Bayesian game is a game that models the outcome of player interactions using aspects of Bayesian probability. Bayesian games are notable because they allowed, for the first time in game theory, for the specification of the solut ...

* Bayesian inference * Bayesian inference in marketing *

Bayesian inference in phylogeny Bayesian inference of phylogeny combines the information in the prior and in the data likelihood to create the so-called posterior probability of trees, which is the probability that the tree is correct given the data, the prior and the likelihood ...

Bayesian inference using Gibbs sampling Bayesian inference using Gibbs sampling (BUGS) is a statistical software for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods. It was developed by David Spiegelhalter at the Medical Research Council Biostatistics Unit i ...

* Bayesian information criterion *

Bayesian linear regression Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables, with the goal of obtaining the posterior probability of the regression coefficients (as well ...

*Bayesian model comparison – see

Bayesian multivariate linear regression In statistics, Bayesian multivariate linear regression is a Bayesian approach to multivariate linear regression, i.e. linear regression where the predicted outcome is a vector of correlated random variables rather than a single scalar random v ...

Bayesian network A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). Bay ...

Bayesian probability Bayesian probability is an interpretation of the concept of probability, in which, instead of frequency or propensity of some phenomenon, probability is interpreted as reasonable expectation representing a state of knowledge or as quantification ...

* Bayesian search theory *

Bayesian spam filtering Naive Bayes classifiers are a popular statistical technique of e-mail filtering. They typically use bag-of-words features to identify email spam, an approach commonly used in text classification. Naive Bayes classifiers work by correlating t ...

Bayesian statistics Bayesian statistics is a theory in the field of statistics based on the Bayesian interpretation of probability where probability expresses a ''degree of belief'' in an event. The degree of belief may be based on prior knowledge about the event, ...

Bayesian tool for methylation analysis Bayesian tool for methylation analysis, also known as BATMAN, is a statistical tool for analysing methylated DNA immunoprecipitation (MeDIP) profiles. It can be applied to large datasets generated using either oligonucleotide arrays (MeDIP-chip) or ...

* Bayesian vector autoregression * BCMP network queueing theory *

Bean machine The Galton board, also known as the Galton box or quincunx or bean machine, is a device invented by Sir Francis Galton to demonstrate the central limit theorem, in particular that with sufficient sample size the binomial distribution approximat ...

Behrens–Fisher distribution In statistics, the Behrens–Fisher distribution, named after Ronald Fisher and Walter Behrens, is a parameterized family of probability distributions arising from the solution of the Behrens–Fisher problem proposed first by Behrens and severa ...

Behrens–Fisher problem In statistics, the Behrens–Fisher problem, named after Walter Behrens and Ronald Fisher, is the problem of interval estimation and hypothesis testing concerning the difference between the means of two normally distributed populations when t ...

Belief propagation A belief is an attitude that something is the case, or that some proposition is true. In epistemology, philosophers use the term "belief" to refer to attitudes about the world which can be either true or false. To believe something is to take i ...

* Belt transect *

Benford's law Benford's law, also known as the Newcomb–Benford law, the law of anomalous numbers, or the first-digit law, is an observation that in many real-life sets of numerical data, the leading digit is likely to be small.Arno Berger and Theodore ...

* Benini distribution * Bennett's inequality *

Berkson error model The Berkson error model is a description of random error (or misclassification) in measurement. Unlike classical error, Berkson error causes little or no bias in the measurement. It was proposed by Joseph Berkson in an article entitled “Are the ...

Berkson's paradox Berkson's paradox, also known as Berkson's bias, collider bias, or Berkson's fallacy, is a result in conditional probability and statistics which is often found to be counterintuitive, and hence a veridical paradox. It is a complicating factor ari ...

* Berlin procedure *

Bernoulli distribution In probability theory and statistics, the Bernoulli distribution, named after Swiss mathematician Jacob Bernoulli,James Victor Uspensky: ''Introduction to Mathematical Probability'', McGraw-Hill, New York 1937, page 45 is the discrete probabi ...

* Bernoulli process *

Bernoulli sampling In the theory of finite population sampling, Bernoulli sampling is a sampling process where each element of the population is subjected to an independent Bernoulli trial which determines whether the element becomes part of the sample. An essential p ...

Bernoulli scheme In mathematics, the Bernoulli scheme or Bernoulli shift is a generalization of the Bernoulli process to more than two possible outcomes. Bernoulli schemes appear naturally in symbolic dynamics, and are thus important in the study of dynamical sy ...

Bernoulli trial In the theory of probability and statistics, a Bernoulli trial (or binomial trial) is a random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success is the same every time the experiment is ...

Bernstein inequalities (probability theory) In probability theory, Bernstein inequalities give bounds on the probability that the sum of random variables deviates from its mean. In the simplest case, let ''X''1, ..., ''X'n'' be independent Bernoulli random variables taking value ...

Bernstein–von Mises theorem In Bayesian inference, the Bernstein-von Mises theorem provides the basis for using Bayesian credible sets for confidence statements in parametric models. It states that under some conditions, a posterior distribution converges in the limit of i ...

* Berry–Esseen theorem *

Bertrand's ballot theorem In combinatorics, Bertrand's ballot problem is the question: "In an election where candidate A receives ''p'' votes and candidate B receives ''q'' votes with ''p'' > ''q'', what is the probability that A will be strictly ahead of B throu ...

* Bertrand's box paradox *

Bessel process In mathematics, a Bessel process, named after Friedrich Bessel, is a type of stochastic process. Formal definition The Bessel process of order ''n'' is the real-valued process ''X'' given (when ''n'' ≥ 2) by :X_t = \, W_t \, , whe ...

Bessel's correction In statistics, Bessel's correction is the use of ''n'' − 1 instead of ''n'' in the formula for the sample variance and sample standard deviation, where ''n'' is the number of observations in a sample. This method corrects the bias in ...

Best linear unbiased prediction In statistics, best linear unbiased prediction (BLUP) is used in linear mixed models for the estimation of random effects. BLUP was derived by Charles Roy Henderson in 1950 but the term "best linear unbiased predictor" (or "prediction") seems not ...

Beta (finance) In finance, the beta (β or market beta or beta coefficient) is a measure of how an individual asset moves (on average) when the overall stock market increases or decreases. Thus, beta is a useful measure of the contribution of an individual a ...

Beta-binomial distribution In probability theory and statistics, the beta-binomial distribution is a family of discrete probability distributions on a finite support of non-negative integers arising when the probability of success in each of a fixed or known number of B ...

Beta-binomial model In probability theory and statistics, the beta-binomial distribution is a family of discrete probability distributions on a finite support of non-negative integers arising when the probability of success in each of a fixed or known number of Bern ...

Beta distribution In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval , 1in terms of two positive parameters, denoted by ''alpha'' (''α'') and ''beta'' (''β''), that appear as ...

Beta function In mathematics, the beta function, also called the Euler integral of the first kind, is a special function that is closely related to the gamma function and to binomial coefficients. It is defined by the integral : \Beta(z_1,z_2) = \int_0^1 t^( ...

for incomplete beta function *

Beta negative binomial distribution In probability theory, a beta negative binomial distribution is the probability distribution of a discrete random variable X equal to the number of failures needed to get r successes in a sequence of independent Bernoulli trials. The probabi ...

Beta prime distribution In probability theory and statistics, the beta prime distribution (also known as inverted beta distribution or beta distribution of the second kindJohnson et al (1995), p 248) is an absolutely continuous probability distribution. Definitions ...

* Beta rectangular distribution * Beverton–Holt model * Bhatia–Davis inequality * Bhattacharya coefficient redirects to

Bhattacharyya distance In statistics, the Bhattacharyya distance measures the similarity of two probability distributions. It is closely related to the Bhattacharyya coefficient which is a measure of the amount of overlap between two statistical samples or populations. ...

Bias (statistics) Statistical bias is a systematic tendency which causes differences between results and facts. The bias exists in numbers of the process of data analysis, including the source of the data, the estimator chosen, and the ways the data was analyzed. ...

Bias of an estimator In statistics, the bias of an estimator (or bias function) is the difference between this estimator's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called ''unbiased''. In s ...

* Biased random walk (biochemistry) *Biased sample – see Sampling bias *

Biclustering Biclustering, block clustering, Co-clustering or two-mode clustering is a data mining technique which allows simultaneous clustering of the rows and columns of a matrix. The term was first introduced by Boris Mirkin to name a technique introduce ...

* Big O in probability notation * Bienaymé–Chebyshev inequality * Bills of Mortality *

Bimodal distribution In statistics, a multimodal distribution is a probability distribution with more than one mode. These appear as distinct peaks (local maxima) in the probability density function, as shown in Figures 1 and 2. Categorical, continuous, and d ...

Binary classification Binary classification is the task of classifying the elements of a set into two groups (each called ''class'') on the basis of a classification rule. Typical binary classification problems include: * Medical testing to determine if a patient has c ...

Bingham distribution In statistics, the Bingham distribution, named after Christopher Bingham, is an antipodally symmetric probability distribution on the ''n''-sphere. It is a generalization of the Watson distribution and a special case of the Kent and Fisher-Bing ...

* Binomial distribution *

Binomial proportion confidence interval In statistics, a binomial proportion confidence interval is a confidence interval for the probability of success calculated from the outcome of a series of success–failure experiments (Bernoulli trial, Bernoulli trials). In other words, a binomia ...

Binomial regression In statistics, binomial regression is a regression analysis technique in which the response (often referred to as ''Y'') has a binomial distribution: it is the number of successes in a series of independent Bernoulli trials, where each trial h ...

Binomial test In statistics, the binomial test is an exact test of the statistical significance of deviations from a theoretically expected distribution of observations into two categories using sample data. Usage The binomial test is useful to test hypoth ...

* Bioinformatics * Biometrics (statistics) redirects to Biostatistics * Biostatistics *

Biplot Biplots are a type of exploratory graph used in statistics, a generalization of the simple two-variable scatterplot. A biplot overlays a ''score plot'' with a ''loading plot''. A biplot allows information on both samples and variables of a d ...

Birnbaum–Saunders distribution The Birnbaum–Saunders distribution, also known as the fatigue life distribution, is a probability distribution used extensively in reliability applications to model failure times. There are several alternative formulations of this distributi ...

* Birth–death process *

Bispectrum In mathematics, in the area of statistical analysis, the bispectrum is a statistic used to search for nonlinear interactions. Definitions The Fourier transform of the second-order cumulant, i.e., the autocorrelation function, is the traditional p ...

* Bivariate analysis *

Bivariate von Mises distribution In probability theory and statistics, the bivariate von Mises distribution is a probability distribution describing values on a torus. It may be thought of as an analogue on the torus of the bivariate normal distribution. The distribution belon ...

* Black–Scholes * Bland–Altman plot *

Blind deconvolution In electrical engineering and applied mathematics, blind deconvolution is deconvolution without explicit knowledge of the impulse response function used in the convolution. This is usually achieved by making appropriate assumptions of the input to ...

Blind experiment In a blind or blinded experiment, information which may influence the participants of the experiment is withheld until after the experiment is complete. Good blinding can reduce or eliminate experimental biases that arise from a participants' expec ...

* Block design *

Blocking (statistics) In the statistical theory of the design of experiments, blocking is the arranging of experimental units in groups (blocks) that are similar to one another. Blocking can be used to tackle the problem of pseudoreplication. Use Blocking reduces un ...

* BMDP software *

Bochner's theorem In mathematics, Bochner's theorem (named for Salomon Bochner) characterizes the Fourier transform of a positive finite Borel measure on the real line. More generally in harmonic analysis, Bochner's theorem asserts that under Fourier transform a c ...

Bonferroni correction In statistics, the Bonferroni correction is a method to counteract the multiple comparisons problem. Background The method is named for its use of the Bonferroni inequalities. An extension of the method to confidence intervals was proposed by Ol ...

Bonferroni inequalities In probability theory, Boole's inequality, also known as the union bound, says that for any finite or countable set of events, the probability that at least one of the events happens is no greater than the sum of the probabilities of the individu ...

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Boole's inequality In probability theory, Boole's inequality, also known as the union bound, says that for any finite or countable set of events, the probability that at least one of the events happens is no greater than the sum of the probabilities of the individu ...

Boolean analysis Boolean analysis was introduced by Flament (1976).Flament, C. (1976). "L'analyse booleenne de questionnaire", Paris: Mouton. The goal of a Boolean analysis is to detect deterministic dependencies between the items of a questionnaire or similar data ...

Bootstrap aggregating Bootstrap aggregating, also called bagging (from bootstrap aggregating), is a machine learning ensemble meta-algorithm designed to improve the stability and accuracy of machine learning algorithms used in statistical classification and regressi ...

Bootstrap error-adjusted single-sample technique In statistics, the bootstrap error-adjusted single-sample technique (BEST or the BEAST) is a Non-parametric statistics, non-parametric method that is intended to allow an assessment to be made of the validity of a single sample. It is based on est ...

* Bootstrapping (statistics) *

Bootstrapping populations Bootstrapping populations in statistics and mathematics starts with a sample \ observed from a random variable. When ''X'' has a given distribution law with a set of non fixed parameters, we denote with a vector \boldsymbol\theta, a parametr ...

Borel–Cantelli lemma In probability theory, the Borel–Cantelli lemma is a theorem about sequences of events. In general, it is a result in measure theory. It is named after Émile Borel and Francesco Paolo Cantelli, who gave statement to the lemma in the first de ...

* Bose–Mesner algebra *

Box–Behnken design In statistics, Box–Behnken designs are experimental designs for response surface methodology, devised by George E. P. Box and Donald Behnken in 1960, to achieve the following goals: * Each factor, or independent variable, is placed at one o ...

* Box–Cox distribution * Box–Cox transformation redirects to

Power transform In statistics, a power transform is a family of functions applied to create a monotonic transformation of data using power functions. It is a data transformation technique used to stabilize variance, make the data more normal distribution-like, i ...

* Box–Jenkins *

Box–Muller transform The Box–Muller transform, by George Edward Pelham Box and Mervin Edgar Muller, is a random number sampling method for generating pairs of independent, standard, normally distributed (zero expectation, unit variance) random numbers, given a ...

* Box–Pierce test *

Box plot In descriptive statistics, a box plot or boxplot is a method for graphically demonstrating the locality, spread and skewness groups of numerical data through their quartiles. In addition to the box on a box plot, there can be lines (which are ca ...

Branching process In probability theory, a branching process is a type of mathematical object known as a stochastic process, which consists of collections of random variables. The random variables of a stochastic process are indexed by the natural numbers. The origi ...

Bregman divergence In mathematics, specifically statistics and information geometry, a Bregman divergence or Bregman distance is a measure of difference between two points, defined in terms of a strictly convex function; they form an important class of divergences. W ...

* Breusch–Godfrey test * Breusch–Pagan statistic redirects to Breusch–Pagan test * Breusch–Pagan test *

Brown–Forsythe test The Brown–Forsythe test is a statistical test for the equality of group variances based on performing an Analysis of Variance (ANOVA) on a transformation of the response variable. When a one-way ANOVA is performed, samples are assumed to have ...

* Brownian bridge *

Brownian excursion In probability theory a Brownian excursion process is a stochastic process that is closely related to a Wiener process (or Brownian motion). Realisations of Brownian excursion processes are essentially just realizations of a Wiener process selecte ...

Brownian motion Brownian motion, or pedesis (from grc, πήδησις "leaping"), is the random motion of particles suspended in a medium (a liquid or a gas). This pattern of motion typically consists of random fluctuations in a particle's position insi ...

Brownian tree In probability theory, the Brownian tree, or Aldous tree, or Continuum Random Tree (CRT) is a special case from random real trees which may be defined from a Brownian excursion. The Brownian tree was defined and studied by David Aldous in three a ...

* Bruck–Ryser–Chowla theorem *

Burke's theorem In queueing theory, a discipline within the mathematical theory of probability, Burke's theorem (sometimes the Burke's output theorem) is a theorem (stated and demonstrated by Paul J. Burke while working at Bell Telephone Laboratories) asserting t ...

Burr distribution In probability theory, statistics and econometrics, the Burr Type XII distribution or simply the Burr distribution is a continuous probability distribution for a non-negative random variable. It is also known as the Singh–Maddala distribution a ...

Business statistics Statistics (from German: ''Statistik'', "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industria ...

Bühlmann model In credibility theory, a branch of study in actuarial science, the Bühlmann model is a random effects model (or "variance components model" or hierarchical linear model) used to determine the appropriate premium for a group of insurance contra ...

Buzen's algorithm In queueing theory, a discipline within the mathematical theory of probability, Buzen's algorithm (or convolution algorithm) is an algorithm for calculating the normalization constant G(''N'') in the Gordon–Newell theorem. This method was first p ...

* BV4.1 (software)

C

* c-chart *

Càdlàg In mathematics, a càdlàg (French: "''continue à droite, limite à gauche''"), RCLL ("right continuous with left limits"), or corlol ("continuous on (the) right, limit on (the) left") function is a function defined on the real numbers (or a subset ...

Calculating demand forecast accuracy Demand forecasting is known as the process of making future estimations in relation to customer demand over a specific period. Generally, demand forecasting will consider historical data and other analytical information to produce the most accurat ...

* Calculus of predispositions * Calibrated probability assessment * Calibration (probability) subjective probability, redirects to Calibrated probability assessment *

Calibration (statistics) There are two main uses of the term calibration in statistics that denote special types of statistical inference problems. "Calibration" can mean :*a reverse process to regression, where instead of a future dependent variable being predicted fro ...

''the statistical calibration problem'' *

Cancer cluster A cancer cluster is a disease cluster in which a high number of cancer cases occurs in a group of people in a particular geographic area over a limited period of time.Candlestick chart A candlestick chart (also called Japanese candlestick chart or K-line) is a style of financial chart used to describe price movements of a security, derivative, or currency. It is similar to a bar chart in that each candlestick represents all f ...

Canonical analysis In statistics, canonical analysis (from grc, κανων bar, measuring rod, ruler) belongs to the family of regression methods for data analysis. Regression analysis quantifies a relationship between a predictor variable and a criterion variable b ...

Canonical correlation In statistics, canonical-correlation analysis (CCA), also called canonical variates analysis, is a way of inferring information from cross-covariance matrices. If we have two vectors ''X'' = (''X''1, ..., ''X'n'') and ''Y' ...

Canopy clustering algorithm The canopy clustering algorithm is an unsupervised pre- clustering algorithm introduced by Andrew McCallum, Kamal Nigam and Lyle Ungar in 2000. It is often used as preprocessing step for the K-means algorithm or the Hierarchical clustering algorithm ...

Cantor distribution The Cantor distribution is the probability distribution whose cumulative distribution function is the Cantor function. This distribution has neither a probability density function nor a probability mass function, since although its cumulativ ...

Carpet plot A carpet plot is any of a few different specific types of plot. The more common plot referred to as a carpet plot is one that illustrates the interaction between two or more independent variables and one or more dependent variables in a two-d ...

Cartogram A cartogram (also called a value-area map or an anamorphic map, the latter common among German-speakers) is a thematic map of a set of features (countries, provinces, etc.), in which their geographic size is altered to be directly proportiona ...

* Case-control redirects to Case-control study * Case-control study *

Catastro of Ensenada In 1749 a large-scale census and statistical investigation was conducted in the Crown of Castile (15.000 castilian places; excluded the Basque provinces, Navarre and the Crown of Aragon). It included population, territorial properties, buildings, ...

a census of part of Spain *

Categorical data In statistics, a categorical variable (also called qualitative variable) is a variable that can take on one of a limited, and usually fixed, number of possible values, assigning each individual or other unit of observation to a particular group or ...

Categorical distribution In probability theory and statistics, a categorical distribution (also called a generalized Bernoulli distribution, multinoulli distribution) is a discrete probability distribution that describes the possible results of a random variable that can ...

* Categorical variable *

Cauchy distribution The Cauchy distribution, named after Augustin Cauchy, is a continuous probability distribution. It is also known, especially among physicists, as the Lorentz distribution (after Hendrik Lorentz), Cauchy–Lorentz distribution, Lorentz(ian) fun ...

* Cauchy–Schwarz inequality * Causal Markov condition * CDF-based nonparametric confidence interval *

Ceiling effect (statistics) The "ceiling effect" is one type of scale attenuation effect; the other scale attenuation effect is the "floor effect". The ceiling effect is observed when an independent variable no longer has an effect on a dependent variable, or the level above ...

Cellular noise Cellular noise is random variability in quantities arising in cellular biology. For example, cells which are genetically identical, even within the same tissue, are often observed to have different expression levels of proteins, different sizes and ...

Censored regression model Censored regression models are a class of models in which the dependent variable is censored above or below a certain threshold. A commonly used likelihood-based model to accommodate to a censored sample is the Tobit model, but quantile and nonp ...

* Censoring (clinical trials) *

Censoring (statistics) In statistics, censoring is a condition in which the value of a measurement or observation is only partially known. For example, suppose a study is conducted to measure the impact of a drug on mortality rate. In such a study, it may be known tha ...

Centering matrix In mathematics and multivariate statistics, the centering matrixJohn I. Marden, ''Analyzing and Modeling Rank Data'', Chapman & Hall, 1995, , page 59. is a symmetric and idempotent matrix, which when multiplied with a vector has the same effect a ...

* Centerpoint (geometry) to which

Tukey median John Wilder Tukey (; June 16, 1915 – July 26, 2000) was an American mathematician and statistician, best known for the development of the fast Fourier Transform (FFT) algorithm and box plot. The Tukey range test, the Tukey lambda distribut ...

redirects * Central composite design *

Central limit theorem In probability theory, the central limit theorem (CLT) establishes that, in many situations, when independent random variables are summed up, their properly normalized sum tends toward a normal distribution even if the original variables themsel ...

** Central limit theorem (illustration) redirects to

Illustration of the central limit theorem In probability theory, the central limit theorem (CLT) states that, in many situations, when independent random variables are added, their properly normalized sum tends toward a normal distribution. This article gives two illustrations of this theor ...

Central limit theorem for directional statistics In probability theory, the central limit theorem states conditions under which the average of a sufficiently large number of independent random variables, each with finite mean and variance, will be approximately normally distributed. Directiona ...

Lyapunov's central limit theorem In probability theory, the central limit theorem (CLT) establishes that, in many situations, when independent random variables are summed up, their properly normalized sum tends toward a normal distribution even if the original variables themselv ...

Martingale central limit theorem In probability theory, the central limit theorem says that, under certain conditions, the sum of many independent identically-distributed random variables, when scaled appropriately, converges in distribution to a standard normal distribution. Th ...

Central moment In probability theory and statistics, a central moment is a moment of a probability distribution of a random variable about the random variable's mean; that is, it is the expected value of a specified integer power of the deviation of the random ...

Central tendency In statistics, a central tendency (or measure of central tendency) is a central or typical value for a probability distribution.Weisberg H.F (1992) ''Central Tendency and Variability'', Sage University Paper Series on Quantitative Applications in ...

Census A census is the procedure of systematically acquiring, recording and calculating information about the members of a given population. This term is used mostly in connection with national population and housing censuses; other common censuses in ...

Cepstrum In Fourier analysis, the cepstrum (; plural ''cepstra'', adjective ''cepstral'') is the result of computing the inverse Fourier transform (IFT) of the logarithm of the estimated signal spectrum. The method is a tool for investigating periodic st ...

* CHAID – CHi-squared Automatic Interaction Detector * Chain rule for Kolmogorov complexity *

Challenge–dechallenge–rechallenge Challenge–dechallenge–rechallenge (CDR) is a medical testing Protocol (natural sciences), protocol in which a medicine or drug is administered, withdrawn, then re-administered, while being monitored for Adverse effect (medicine), adverse effec ...

* Champernowne distribution *

Change detection In statistical analysis, change detection or change point detection tries to identify times when the probability distribution of a stochastic process or time series changes. In general the problem concerns both detecting whether or not a change ...

** Change detection (GIS) * Chapman–Kolmogorov equation * Chapman–Robbins bound *

Characteristic function (probability theory) In probability theory and statistics, the characteristic function of any real-valued random variable completely defines its probability distribution. If a random variable admits a probability density function, then the characteristic function ...

Chauvenet's criterion In statistical theory, Chauvenet's criterion (named for William Chauvenet) is a means of assessing whether one piece of experimental data — an outlier — from a set of observations, is likely to be spurious. Derivation The idea behind ...

Chebyshev center In geometry, the Chebyshev center of a bounded set Q having non-empty Interior (topology), interior is the center of the minimal-radius ball enclosing the entire set Q, or alternatively (and non-equivalently) the center of largest inscribed ball ...

Chebyshev's inequality In probability theory, Chebyshev's inequality (also called the Bienaymé–Chebyshev inequality) guarantees that, for a wide class of probability distributions, no more than a certain fraction of values can be more than a certain distance from th ...

Checking if a coin is biased In statistics, the question of checking whether a coin is fair is one whose importance lies, firstly, in providing a simple problem on which to illustrate basic ideas of statistical inference and, secondly, in providing a simple problem that can ...

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Checking whether a coin is fair In statistics, the question of checking whether a coin is fair is one whose importance lies, firstly, in providing a simple problem on which to illustrate basic ideas of statistical inference and, secondly, in providing a simple problem that can be ...

Cheeger bound In mathematics, the Cheeger bound is a bound of the second largest eigenvalue of the transition matrix of a finite-state, discrete-time, reversible stationary Markov chain. It can be seen as a special case of Cheeger inequalities in expander graph ...

Chemometrics Chemometrics is the science of extracting information from chemical systems by data-driven means. Chemometrics is inherently interdisciplinary, using methods frequently employed in core data-analytic disciplines such as multivariate statistics, a ...

Chernoff bound In probability theory, the Chernoff bound gives exponentially decreasing bounds on tail distributions of sums of independent random variables. Despite being named after Herman Chernoff, the author of the paper it first appeared in, the result is d ...

a special case of Chernoff's inequality * Chernoff face * Chernoff's distribution * Chernoff's inequality *

Chi distribution In probability theory and statistics, the chi distribution is a continuous probability distribution. It is the distribution of the positive square root of the sum of squares of a set of independent random variables each following a standard norm ...

Chi-squared distribution In probability theory and statistics, the chi-squared distribution (also chi-square or \chi^2-distribution) with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables. The chi-squar ...

Chi-squared test A chi-squared test (also chi-square or test) is a statistical hypothesis test used in the analysis of contingency tables when the sample sizes are large. In simpler terms, this test is primarily used to examine whether two categorical variables ...

* Chinese restaurant process *

Choropleth map A choropleth map () is a type of statistical thematic map that uses pseudocolor, i.e., color corresponding with an aggregate summary of a geographic characteristic within spatial enumeration units, such as population density or per-capita inc ...

* Chou's invariance theorem *

Chow test The Chow test (), proposed by econometrician Gregory Chow in 1960, is a test of whether the true coefficients in two linear regressions on different data sets are equal. In econometrics, it is most commonly used in time series analysis to test fo ...

* Chronux software * Circular analysis *

Circular distribution In probability and statistics, a circular distribution or polar distribution is a probability distribution of a random variable whose values are angles, usually taken to be in the range A circular distribution is often a continuous probability ...

* Circular error probable *

Circular statistics Directional statistics (also circular statistics or spherical statistics) is the subdiscipline of statistics that deals with directions (unit vectors in Euclidean space, R''n''), axes ( lines through the origin in R''n'') or rotations in R''n''. Mo ...

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Directional statistics Directional statistics (also circular statistics or spherical statistics) is the subdiscipline of statistics that deals with directions (unit vectors in Euclidean space, R''n''), axes (lines through the origin in R''n'') or rotations in R''n''. M ...

Circular uniform distribution In probability theory and directional statistics, a circular uniform distribution is a probability distribution on the unit circle whose density is uniform for all angles. Description Definition The probability density function (pdf) of the c ...

* Civic statistics *

Clark–Ocone theorem In mathematics, the Clark–Ocone theorem (also known as the Clark–Ocone–Haussmann theorem or formula) is a theorem of stochastic analysis. It expresses the value of some function ''F'' defined on the classical Wiener space of continuous paths ...

Class membership probabilities In machine learning, a probabilistic classifier is a classifier that is able to predict, given an observation of an input, a probability distribution over a set of classes, rather than only outputting the most likely class that the observation sho ...

* Classic data sets *

Classical definition of probability The classical definition or interpretation of probability is identified with the works of Jacob Bernoulli and Pierre-Simon Laplace. As stated in Laplace's ''Théorie analytique des probabilités'', :The probability of an event is the ratio of the n ...

Classical test theory Classical test theory (CTT) is a body of related psychometric theory that predicts outcomes of psychological testing such as the difficulty of items or the ability of test-takers. It is a theory of testing based on the idea that a person's observe ...

– psychometrics *

Classification rule Given a population whose members each belong to one of a number of different sets or classes, a classification rule or classifier is a procedure by which the elements of the population set are each predicted to belong to one of the classes. A perfe ...

* Classifier (mathematics) * Climate ensemble * Climograph * Clinical significance *

Clinical study design Clinical study design is the formulation of trials and experiments, as well as observational studies in medical, clinical and other types of research (e.g., epidemiological) involving human beings. The goal of a clinical study is to assess the saf ...

Clinical trial Clinical trials are prospective biomedical or behavioral research studies on human participants designed to answer specific questions about biomedical or behavioral interventions, including new treatments (such as novel vaccines, drugs, diet ...

* Clinical utility of diagnostic tests *

Cliodynamics Cliodynamics () is a transdisciplinary area of research that integrates cultural evolution, economic history/cliometrics, macrosociology, the mathematical modeling of historical processes during the ''longue durée'', and the construction and analy ...

* Closed testing procedure * Cluster analysis *

Cluster randomised controlled trial A cluster-randomised controlled trial is a type of randomised controlled trial in which groups of subjects (as opposed to individual subjects) are randomised. Cluster randomised controlled trials are also known as cluster-randomised trials, group-ra ...

* Cluster sampling *

Cluster-weighted modeling In data mining, cluster-weighted modeling (CWM) is an algorithm-based approach to non-linear prediction of outputs ( dependent variables) from inputs (independent variables) based on density estimation using a set of models (clusters) that are each ...

Clustering high-dimensional data Clustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions. Such high-dimensional spaces of data are often encountered in areas such as medicine, where DNA microarray technology ...

CMA-ES Covariance matrix adaptation evolution strategy (CMA-ES) is a particular kind of strategy for numerical optimization. Evolution strategies (ES) are stochastic, derivative-free methods for numerical optimization of non-linear or non-convex continu ...

(Covariance Matrix Adaptation Evolution Strategy) * Coalescent theory * Cochran's C test *

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 id ...

Cochran's theorem In statistics, Cochran's theorem, devised by William G. Cochran, is a theorem used to justify results relating to the probability distributions of statistics that are used in the analysis of variance. Statement Let ''U''1, ..., ''U'N'' be i.i. ...

* Cochran–Armitage test for trend *

Cochran–Mantel–Haenszel statistics In statistics, the Cochran–Mantel–Haenszel test (CMH) is a test used in the analysis of stratified or matched categorical data. It allows an investigator to test the association between a binary predictor or treatment and a binary outcome such ...

Cochrane–Orcutt estimation Cochrane–Orcutt estimation is a procedure in econometrics, which adjusts a linear model for serial correlation in the error term. Developed in the 1940s, it is named after statisticians Donald Cochrane and Guy Orcutt. Theory Consider the mode ...

Coding (social sciences) Coding may refer to: Computer science * Computer programming, the process of creating and maintaining the source code of computer programs * Line coding, in data storage * Source coding, compression used in data transmission * Coding theory * Cha ...

* Coefficient of coherence redirects to Coherence (statistics) * Coefficient of determination * Coefficient of dispersion * Coefficient of variation * Cognitive pretesting * Cohen's class distribution function – a time-frequency distribution function *

Cohen's kappa Cohen's kappa coefficient (''κ'', lowercase Greek kappa) is a statistic that is used to measure inter-rater reliability (and also intra-rater reliability) for qualitative (categorical) items. It is generally thought to be a more robust measure th ...

Coherence (signal processing) In signal processing, the coherence is a statistic that can be used to examine the relation between two signals or data sets. It is commonly used to estimate the power transfer between input and output of a linear system. If the signals are ergodi ...

* Coherence (statistics) *

Cohort (statistics) In statistics, marketing and demography, a cohort is a group of subjects who share a defining characteristic (typically subjects who experienced a common event in a selected time period, such as birth or graduation). Cohort data can oftentimes ...

Cohort effect The term cohort effect is used in social science to describe variations in the characteristics of an area of study (such as the incidence of a characteristic or the age at onset) over time among individuals who are defined by some shared temporal ex ...

Cohort study A cohort study is a particular form of longitudinal study that samples a cohort (a group of people who share a defining characteristic, typically those who experienced a common event in a selected period, such as birth or graduation), performing ...

Cointegration Cointegration is a statistical property of a collection of time series variables. First, all of the series must be integrated of order ''d'' (see Order of integration). Next, if a linear combination of this collection is integrated of order less ...

Collectively exhaustive events In probability theory and logic, a set of events is jointly or collectively exhaustive if at least one of the events must occur. For example, when rolling a six-sided die, the events 1, 2, 3, 4, 5, and 6 balls of a single outcome are collecti ...

Collider (epidemiology) In statistics and causal graphs, a variable is a collider when it is causally influenced by two or more variables. The name "collider" reflects the fact that in graphical models, the arrow heads from variables that lead into the collider appear to ...

Combinatorial data analysis In statistics, combinatorial data analysis (CDA) is the study of data sets where the order in which objects are arranged is important. CDA can be used either to determine how well a given combinatorial construct reflects the observed data, or to sea ...

Combinatorial design Combinatorial design theory is the part of combinatorial mathematics that deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of ''balance'' and/or ''symmetry''. These co ...

Combinatorial meta-analysis Combinatorial meta-analysis (CMA) is the study of the behaviour of statistical properties of combinations of studies from a meta-analytic dataset (typically in social science research). In an article that develops the notion of "gravity" in the co ...

* Common-method variance *

Common mode failure Common and special causes are the two distinct origins of variation in a process, as defined in the statistical thinking and methods of Walter A. Shewhart and W. Edwards Deming. Briefly, "common causes", also called natural patterns, are the ...

Common cause and special cause (statistics) Common and special causes are the two distinct origins of variation in a process, as defined in the statistical thinking and methods of Walter A. Shewhart and W. Edwards Deming. Briefly, "common causes", also called natural patterns, are the ...

Comonotonicity In probability theory, comonotonicity mainly refers to the perfect positive dependence between the components of a random vector, essentially saying that they can be represented as increasing functions of a single random variable. In two dimensions ...

* Comparing means * Comparison of general and generalized linear models *

Comparison of statistical packages The following tables compare general and technical information for a number of statistical analysis packages. General information Operating system support ANOVA Support for various ANOVA methods Regression Support for various regression ...

* Comparisonwise error rate *

Complementary event In probability theory, the complement of any event ''A'' is the event ot ''A'' i.e. the event that ''A'' does not occur.Robert R. Johnson, Patricia J. Kuby: ''Elementary Statistics''. Cengage Learning 2007, , p. 229 () The event ''A'' and ...

Complete-linkage clustering Complete-linkage clustering is one of several methods of agglomerative hierarchical clustering. At the beginning of the process, each element is in a cluster of its own. The clusters are then sequentially combined into larger clusters until all ...

Complete spatial randomness Complete spatial randomness (CSR) describes a point process whereby point events occur within a given study area in a completely random fashion. It is synonymous with a ''homogeneous spatial Poisson process''.O. Maimon, L. Rokach, ''Data Mining an ...

Completely randomized design In the design of experiments, completely randomized designs are for studying the effects of one primary factor without the need to take other nuisance variables into account. This article describes completely randomized designs that have one primar ...

* Completeness (statistics) *

Compositional data In statistics, compositional data are quantitative descriptions of the parts of some whole, conveying relative information. Mathematically, compositional data is represented by points on a simplex. Measurements involving probabilities, proportions, ...

* Composite bar chart *

Compound Poisson distribution In probability theory, a compound Poisson distribution is the probability distribution of the sum of a number of independent identically-distributed random variables, where the number of terms to be added is itself a Poisson-distributed variable. ...

Compound Poisson process A compound Poisson process is a continuous-time (random) stochastic process with jumps. The jumps arrive randomly according to a Poisson process and the size of the jumps is also random, with a specified probability distribution. A compound Poisso ...

Compound probability distribution In probability and statistics, a compound probability distribution (also known as a mixture distribution or contagious distribution) is the probability distribution that results from assuming that a random variable is distributed according to som ...

*Computational formula for the variance *

Computational learning theory In computer science, computational learning theory (or just learning theory) is a subfield of artificial intelligence devoted to studying the design and analysis of machine learning algorithms. Overview Theoretical results in machine learning m ...

Computational statistics Computational statistics, or statistical computing, is the bond between statistics and computer science. It means statistical methods that are enabled by using computational methods. It is the area of computational science (or scientific computin ...

Computer experiment A computer experiment or simulation experiment is an experiment used to study a computer simulation, also referred to as an in silico system. This area includes computational physics, computational chemistry, computational biology and other similar ...

Computer-assisted survey information collection Computer-assisted survey information collection (CASIC) refers to a variety of survey modes that were enabled by the introduction of computer technology. The first CASIC modes were interviewer-administered, while later on computerized self-administ ...

Concomitant (statistics) In statistics, the concept of a concomitant, also called the induced order statistic, arises when one sorts the members of a random sample according to corresponding values of another random sample. Let (''X'i'', ''Y'i''), ''i'' =&n ...

Concordance correlation coefficient In statistics, the concordance correlation coefficient measures the agreement between two variables, e.g., to evaluate reproducibility or for inter-rater reliability. Definition The form of the concordance correlation coefficient \rho_c as :\rho_c ...

Concordant pair In statistics, a concordant pair is a pair of observations, each on two variables, (X''1'',Y''1'') and (X''2'',Y''2''), having the property that : \sgn (X_2 - X_1)\ = \sgn (Y_2 - Y_1), where "sgn" refers to whether a number is positive, zero, ...

* Concrete illustration of the central limit theorem *

Concurrent validity Concurrent validity is a type of evidence that can be gathered to defend the use of a test for predicting other outcomes. It is a parameter used in sociology, psychology, and other psychometric or behavioral sciences. Concurrent validity is demonst ...

* Conditional change model *Conditional distribution – see

Conditional probability distribution In probability theory and statistics, given two jointly distributed random variables X and Y, the conditional probability distribution of Y given X is the probability distribution of Y when X is known to be a particular value; in some cases the ...

Conditional dependence In probability theory, conditional dependence is a relationship between two or more events that are dependent when a third event occurs.Introduction to Artificial Intelligence by Sebastian Thrun and Peter Norvig, 201"Unit 3: Conditional Depende ...

* Conditional expectation *

Conditional independence In probability theory, conditional independence describes situations wherein an observation is irrelevant or redundant when evaluating the certainty of a hypothesis. Conditional independence is usually formulated in terms of conditional probabil ...

Conditional probability In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption, assertion or evidence) has already occurred. This particular method relies on event B occu ...

Conditional random field Conditional random fields (CRFs) are a class of statistical modeling methods often applied in pattern recognition and machine learning and used for structured prediction. Whereas a classifier predicts a label for a single sample without consid ...

Conditional variance In probability theory and statistics, a conditional variance is the variance of a random variable given the value(s) of one or more other variables. Particularly in econometrics, the conditional variance is also known as the scedastic function or ...

* Conditionality principle *

Confidence band A confidence band is used in statistical analysis to represent the uncertainty in an estimate of a curve or function based on limited or noisy data. Similarly, a prediction band is used to represent the uncertainty about the value of a new data-p ...

redirects to Confidence and prediction bands *

Confidence distribution In statistical inference, the concept of a confidence distribution (CD) has often been loosely referred to as a distribution function on the parameter space that can represent confidence intervals of all levels for a parameter of interest. Histori ...

* Confidence interval * Confidence region * Configural frequency analysis * Confirmation bias *

Confirmatory factor analysis In statistics, confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social science research.Kline, R. B. (2010). ''Principles and practice of structural equation modeling (3rd ed.).'' New York, New York: Gu ...

* Confounding *

Confounding factor In statistics, a confounder (also confounding variable, confounding factor, extraneous determinant or lurking variable) is a variable that influences both the dependent variable and independent variable, causing a spurious association. Con ...

* Confusion of the inverse *

Congruence coefficient In multivariate statistics, the congruence coefficient is an index of the similarity between factors that have been derived in a factor analysis. It was introduced in 1948 by Cyril Burt who referred to it as ''unadjusted correlation''. It is also ca ...

Conjoint analysis Conjoint analysis is a survey-based statistical technique used in market research that helps determine how people value different attributes (feature, function, benefits) that make up an individual product or service. The objective of conjoint an ...

** Conjoint analysis (in healthcare) ** Conjoint analysis (in marketing) *

Conjugate prior In Bayesian probability theory, if the posterior distribution p(\theta \mid x) is in the same probability distribution family as the prior probability distribution p(\theta), the prior and posterior are then called conjugate distributions, and th ...

Consensus-based assessment Consensus-based assessment expands on the common practice of consensus decision-making and the theoretical observation that expertise can be closely approximated by large numbers of novices or journeymen. It creates a method for determining measure ...

Consensus clustering Consensus clustering is a method of aggregating (potentially conflicting) results from multiple clustering algorithms. Also called cluster ensembles or aggregation of clustering (or partitions), it refers to the situation in which a number of differ ...

Consensus forecast Used in a number of sciences, ranging from econometrics to meteorology, consensus forecasts are predictions of the future that are created by combining together several separate forecasts which have often been created using different methodologies ...

* Conservatism (belief revision) * Consistency (statistics) *

Consistent estimator In statistics, a consistent estimator or asymptotically consistent estimator is an estimator—a rule for computing estimates of a parameter ''θ''0—having the property that as the number of data points used increases indefinitely, the result ...

Constant elasticity of substitution Constant elasticity of substitution (CES), in economics, is a property of some production functions and utility functions. Several economists have featured in the topic and have contributed in the final finding of the constant. They include Tom McK ...

* Constant false alarm rate * Constraint (information theory) * Consumption distribution * Contact process (mathematics) *

Content validity In psychometrics, content validity (also known as logical validity) refers to the extent to which a measure represents all facets of a given construct. For example, a depression scale may lack content validity if it only assesses the affective dim ...

Contiguity (probability theory) In probability theory, two sequences of probability measures are said to be contiguous if asymptotically they share the same support. Thus the notion of contiguity extends the concept of absolute continuity to the sequences of measures. The conce ...

* Contingency table *

Continuity correction In probability theory, a continuity correction is an adjustment that is made when a discrete distribution is approximated by a continuous distribution. Examples Binomial If a random variable ''X'' has a binomial distribution with parameters ' ...

*Continuous distribution – see

Continuous probability distribution In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment. It is a mathematical description of a random phenomenon ...

Continuous mapping theorem In probability theory, the continuous mapping theorem states that continuous functions preserve limits even if their arguments are sequences of random variables. A continuous function, in Heine’s definition, is such a function that maps converg ...

Continuous stochastic process In probability theory, a continuous stochastic process is a type of stochastic process that may be said to be " continuous" as a function of its "time" or index parameter. Continuity is a nice property for (the sample paths of) a process to have ...

Continuous-time Markov process A continuous-time Markov chain (CTMC) is a continuous stochastic process in which, for each state, the process will change state according to an exponential random variable and then move to a different state as specified by the probabilities of ...

Continuous-time stochastic process In probability theory and statistics, a continuous-time stochastic process, or a continuous-space-time stochastic process is a stochastic process for which the index variable takes a continuous set of values, as contrasted with a discrete-time pr ...

* Contrast (statistics) *

Control chart Control charts is a graph used in production control to determine whether quality and manufacturing processes are being controlled under stable conditions. (ISO 7870-1) The hourly status is arranged on the graph, and the occurrence of abnormalit ...

* Control event rate *

Control limits Process Window Index (PWI) is a statistical measure that quantifies the robustness of a manufacturing process, e.g. one which involves heating and cooling, known as a thermal process. In manufacturing industry, PWI values are used to calibrate t ...

Control variate The control variates method is a variance reduction technique used in Monte Carlo methods. It exploits information about the errors in estimates of known quantities to reduce the error of an estimate of an unknown quantity. Glasserman, P. (2004). ...

Controlling for a variable In causal models, controlling for a variable means binning data according to measured values of the variable. This is typically done so that the variable can no longer act as a confounder in, for example, an observational study or experiment. ...

Convergence of measures In mathematics, more specifically measure theory, there are various notions of the convergence of measures. For an intuitive general sense of what is meant by ''convergence of measures'', consider a sequence of measures μ''n'' on a space, sharing ...

Convergence of random variables In probability theory, there exist several different notions of convergence of random variables. The convergence of sequences of random variables to some limit random variable is an important concept in probability theory, and its applications to ...

* Convex hull * Convolution of probability distributions *

Convolution random number generator In statistics and computer software, a convolution random number generator is a pseudo-random number sampling method that can be used to generate random variates from certain classes of probability distribution. The particular advantage of this ...

Conway–Maxwell–Poisson distribution In probability theory and statistics, the Conway–Maxwell–Poisson (CMP or COM–Poisson) distribution is a discrete probability distribution named after Richard W. Conway, William L. Maxwell, and Siméon Denis Poisson that generalizes the P ...

Cook's distance In statistics, Cook's distance or Cook's ''D'' is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis. In a practical ordinary least squares analysis, Cook's distance can be used in several ...

Cophenetic correlation In statistics, and especially in biostatistics, cophenetic correlation (more precisely, the cophenetic correlation coefficient) is a measure of how faithfully a dendrogram preserves the pairwise distances between the original unmodeled data points. ...

Copula (statistics) In probability theory and statistics, a copula is a multivariate cumulative distribution function for which the marginal probability distribution of each variable is uniform on the interval , 1 Copulas are used to describe/model the ...

* Cornish–Fisher expansion *

Correct sampling During sampling of granular materials (whether airborne, suspended in liquid, aerosol, or aggregated), correct sampling is defined in Gy's sampling theory as a sampling scenario in which all particles in a population have the same probability of ...

Correction for attenuation Regression dilution, also known as regression attenuation, is the biasing of the linear regression slope towards zero (the underestimation of its absolute value), caused by errors in the independent variable. Consider fitting a straight line for ...

* Correlation * Correlation and dependence * Correlation does not imply causation *

Correlation clustering Clustering is the problem of partitioning data points into groups based on their similarity. Correlation clustering provides a method for clustering a set of objects into the optimum number of clusters without specifying that number in advance. De ...

* Correlation function **

Correlation function (astronomy) In astronomy, a correlation function describes the distribution of galaxies in the universe. By default, "correlation function" refers to the two-point autocorrelation function. The two-point autocorrelation function is a function of one varia ...

Correlation function (quantum field theory) In quantum field theory, correlation functions, often referred to as correlators or Green's functions, are vacuum expectation values of time-ordered products of field operators. They are a key object of study in quantum field theory where they ...

Correlation function (statistical mechanics) In statistical mechanics, the correlation function is a measure of the order in a system, as characterized by a mathematical correlation function. Correlation functions describe how microscopic variables, such as spin and density, at different p ...

* Correlation inequality *

Correlation ratio In statistics, the correlation ratio is a measure of the curvilinear relationship between the statistical dispersion within individual categories and the dispersion across the whole population or sample. The measure is defined as the ''ratio'' of t ...

* Correspondence analysis *

Cosmic variance The term ''cosmic variance'' is the statistical uncertainty inherent in observations of the universe at extreme distances. It has three different but closely related meanings: * It is sometimes used, incorrectly, to mean sample variance – the d ...

* Cost-of-living index * Count data *

Counternull In statistics, and especially in the statistical analysis of psychological data, the counternull is a statistic used to aid the understanding and presentation of research results. It revolves around the effect size, which is the mean magnitude of so ...

Counting process A counting process is a stochastic process with values that are non-negative, integer, and non-decreasing: # ''N''(''t'') ≥ 0. # ''N''(''t'') is an integer. # If ''s'' ≤ ''t'' then ''N''(''s'') ≤ ''N''(''t''). If ''s'' < ''t'', then ''N''(' ...

Covariance In probability theory and statistics, covariance is a measure of the joint variability of two random variables. If the greater values of one variable mainly correspond with the greater values of the other variable, and the same holds for the ...

Covariance and correlation In probability theory and statistics, the mathematical concepts of covariance and correlation are very similar. Both describe the degree to which two random variables or sets of random variables tend to deviate from their expected values in ...

Covariance intersection Covariance intersection is an algorithm for combining two or more estimates of state variables in a Kalman filter when the correlation between them is unknown. Specification Items of information a and b are known and are to be fused into informat ...

* Covariance matrix *

Covariance function In probability theory and statistics, the covariance function describes how much two random variables change together (their ''covariance'') with varying spatial or temporal separation. For a random field or stochastic process ''Z''(''x'') on a ...

Covariate Dependent and independent variables are variables in mathematical modeling, statistical modeling and experimental sciences. Dependent variables receive this name because, in an experiment, their values are studied under the supposition or deman ...

* Cover's theorem * Coverage probability *

Cox process In probability theory, a Cox process, also known as a doubly stochastic Poisson process is a point process which is a generalization of a Poisson process where the intensity that varies across the underlying mathematical space (often space or time ...

Cox's theorem Cox's theorem, named after the physicist Richard Threlkeld Cox, is a derivation of the laws of probability theory from a certain set of postulates. This derivation justifies the so-called "logical" interpretation of probability, as the laws of p ...

Cox–Ingersoll–Ross model In mathematical finance, the Cox–Ingersoll–Ross (CIR) model describes the evolution of interest rates. It is a type of "one factor model" ( short-rate model) as it describes interest rate movements as driven by only one source of mark ...

Cramér–Rao bound In estimation theory and statistics, the Cramér–Rao bound (CRB) expresses a lower bound on the variance of unbiased estimators of a deterministic (fixed, though unknown) parameter, the variance of any such estimator is at least as high as the ...

Cramér–von Mises criterion In statistics the Cramér–von Mises criterion is a criterion used for judging the goodness of fit of a cumulative distribution function F^* compared to a given empirical distribution function F_n, or for comparing two empirical distributions. ...

* Cramér’s decomposition theorem * Cramér's theorem (large deviations) *

Cramér's V In statistics, Cramér's V (sometimes referred to as Cramér's phi and denoted as φ''c'') is a measure of association between two nominal variables, giving a value between 0 and +1 (inclusive). It is based on Pearson's chi-squared statistic and ...

* Craps principle *

Credal set A credal set is a set of probability distributions or, more generally, a set of (possibly finitely additive) probability measures. A credal set is often assumed or constructed to be a closed convex set. It is intended to express uncertainty or ...

Credible interval In Bayesian statistics, a credible interval is an interval within which an unobserved parameter value falls with a particular probability. It is an interval in the domain of a posterior probability distribution or a predictive distribution. T ...

Cricket statistics Cricket is a sport that generates a variety of statistics. Statistics are recorded for each player during a match, and aggregated over a career. At the professional level, statistics for Test cricket, one-day internationals, and first-class cric ...

* Crime statistics *

Critical region A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. ...

redirects to Statistical hypothesis testing *

Cromwell's rule Cromwell's rule, named by statistician Dennis Lindley, states that the use of prior probabilities of 1 ("the event will definitely occur") or 0 ("the event will definitely not occur") should be avoided, except when applied to statements that ar ...

* Cronbach's α * Cross-correlation * Cross-covariance *

Cross-entropy method The cross-entropy (CE) method is a Monte Carlo method for importance sampling and optimization. It is applicable to both combinatorial and continuous problems, with either a static or noisy objective. The method approximates the optimal importance ...

Cross-sectional data Cross-sectional data, or a cross section of a study population, in statistics and econometrics, is a type of data collected by observing many subjects (such as individuals, firms, countries, or regions) at the one point or period of time. The anal ...

Cross-sectional regression In statistics and econometrics, a cross-sectional regression is a type of regression in which the explained and explanatory variables are all associated with the same single period or point in time. This type of cross-sectional analysis is in con ...

Cross-sectional study In medical research, social science, and biology, a cross-sectional study (also known as a cross-sectional analysis, transverse study, prevalence study) is a type of observational study that analyzes data from a population, or a representative su ...

* Cross-spectrum *

Cross tabulation In statistics, a contingency table (also known as a cross tabulation or crosstab) is a type of table in a matrix format that displays the (multivariate) frequency distribution of the variables. They are heavily used in survey research, business ...

Cross-validation (statistics) Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how the results of a statistical analysis will generalize to an independent data set. Cross-va ...

Crossover study In medicine, a crossover study or crossover trial is a longitudinal study in which subjects receive a sequence of different treatments (or exposures). While crossover studies can be observational studies, many important crossover studies are con ...

* Crystal Ball function – a probability distribution *

Cumulant In probability theory and statistics, the cumulants of a probability distribution are a set of quantities that provide an alternative to the '' moments'' of the distribution. Any two probability distributions whose moments are identical will have ...

* Cumulant generating function redirects to

cumulant In probability theory and statistics, the cumulants of a probability distribution are a set of quantities that provide an alternative to the '' moments'' of the distribution. Any two probability distributions whose moments are identical will have ...

* Cumulative accuracy profile * Cumulative distribution function *

Cumulative frequency analysis Cumulative frequency analysis is the analysis of the frequency of occurrence of values of a phenomenon less than a reference value. The phenomenon may be time- or space-dependent. Cumulative frequency is also called ''frequency of non-exceedance ...

Cumulative incidence In epidemiology, incidence is a measure of the probability of occurrence of a given medical condition in a population within a specified period of time. Although sometimes loosely expressed simply as the number of new cases during some time pe ...

* Cunningham function * CURE data clustering algorithm *

Curve fitting Curve fitting is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, possibly subject to constraints. Curve fitting can involve either interpolation, where an exact fit to the data i ...

CUSUM In statistical quality control, the CUsUM (or cumulative sum control chart) is a sequential analysis technique developed by E. S. Page of the University of Cambridge. It is typically used for monitoring change detection. CUSUM was announced in ...

* Cuzick–Edwards test *

Cyclostationary process A cyclostationary process is a signal having statistical properties that vary cyclically with time. A cyclostationary process can be viewed as multiple interleaved stationary processes. For example, the maximum daily temperature in New York City ca ...

D

d-separation A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). Bay ...

* D/M/1 queue *

D'Agostino's K-squared test In statistics, D'Agostino's ''K''2 test, named for Ralph D'Agostino, is a goodness-of-fit measure of departure from normality, that is the test aims to gauge the compatibility of given data with the null hypothesis that the data is a realizatio ...

Dagum distribution The Dagum distribution (or Mielke Beta-Kappa distribution) is a continuous probability distribution defined over positive real numbers. It is named after Camilo Dagum, who proposed it in a series of papers in the 1970s. The Dagum distribution ar ...

* DAP open source software * Data analysis *

Data assimilation Data assimilation is a mathematical discipline that seeks to optimally combine theory (usually in the form of a numerical model) with observations. There may be a number of different goals sought – for example, to determine the optimal state es ...

Data binning Data binning, also called data discrete binning or data bucketing, is a data pre-processing technique used to reduce the effects of minor observation errors. The original data values which fall into a given small interval, a '' bin'', are replaced b ...

Data classification (business intelligence) In business intelligence, data classification has close ties to data clustering, but where data clustering is ''descriptive'', data classification is ''predictive''. In essence data classification consists of using variables with known values to ...

Data cleansing Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the d ...

Data clustering Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of ...

* Data collection * Data Desk software * Data dredging *

Data fusion Data fusion is the process of integrating multiple data sources to produce more consistent, accurate, and useful information than that provided by any individual data source. Data fusion processes are often categorized as low, intermediate, or hig ...

* Data generating process * Data mining *

Data reduction Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. The purpose of data reduction can be two-fold: reduce the number of data rec ...

Data point In statistics, a unit of observation is the unit described by the data that one analyzes. A study may treat groups as a unit of observation with a country as the unit of analysis, drawing conclusions on group characteristics from data collected at ...

* Data quality assurance *

Data set A data set (or dataset) is a collection of data. In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the ...

Data-snooping bias Data dredging (also known as data snooping or ''p''-hacking) is the misuse of data analysis to find patterns in data that can be presented as statistically significant, thus dramatically increasing and understating the risk of false positives. T ...

* Data stream clustering *

Data transformation (statistics) In statistics, data transformation is the application of a deterministic mathematical function to each point in a data set—that is, each data point ''zi'' is replaced with the transformed value ''yi'' = ''f''(''zi''), where ''f'' is a functi ...

* Data visualization * DataDetective software * Dataplot software * Davies–Bouldin index * Davis distribution * De Finetti's game *

De Finetti's theorem In probability theory, de Finetti's theorem states that exchangeable observations are conditionally independent relative to some latent variable. An epistemic probability distribution could then be assigned to this variable. It is named in hono ...

* DeFries–Fulker regression * de Moivre's law *

De Moivre–Laplace theorem In probability theory, the de Moivre–Laplace theorem, which is a special case of the central limit theorem, states that the normal distribution may be used as an approximation to the binomial distribution under certain conditions. In particu ...

Decision boundary __NOTOC__ In a statistical-classification problem with two classes, a decision boundary or decision surface is a hypersurface that partitions the underlying vector space into two sets, one for each class. The classifier will classify all the point ...

Decision theory Decision theory (or the theory of choice; not to be confused with choice theory) is a branch of applied probability theory concerned with the theory of making decisions based on assigning probabilities to various factors and assigning numerical ...

Decomposition of time series The decomposition of time series is a statistical task that deconstructs a time series into several components, each representing one of the underlying categories of patterns. There are two principal types of decomposition, which are outlined belo ...

Degenerate distribution In mathematics, a degenerate distribution is, according to some, a probability distribution in a space with support only on a manifold of lower dimension, and according to others a distribution with support only at a single point. By the latter d ...

Degrees of freedom (statistics) In statistics, the number of degrees of freedom is the number of values in the final calculation of a statistic that are free to vary. Estimates of statistical parameters can be based upon different amounts of information or data. The number of i ...

* Delaporte distribution *

Delphi method } The Delphi method or Delphi technique ( ; also known as Estimate-Talk-Estimate or ETE) is a structured communication technique or method, originally developed as a systematic, interactive forecasting method which relies on a panel of experts. The ...

Delta method In statistics, the delta method is a result concerning the approximate probability distribution for a function of an asymptotically normal statistical estimator from knowledge of the limiting variance of that estimator. History The delta meth ...

Demand forecasting Demand forecasting is known as the process of making future estimations in relation to customer demand over a specific period. Generally, demand forecasting will consider historical data and other analytical information to produce the most accurat ...

Deming regression In statistics, Deming regression, named after W. Edwards Deming, is an errors-in-variables model which tries to find the line of best fit for a two-dimensional dataset. It differs from the simple linear regression in that it accounts for erro ...

Demographics Demography () is the statistical study of populations, especially human beings. Demographic analysis examines and measures the dimensions and dynamics of populations; it can cover whole societies or groups defined by criteria such as ed ...

Demography Demography () is the statistical study of populations, especially human beings. Demographic analysis examines and measures the dimensions and dynamics of populations; it can cover whole societies or groups defined by criteria such as edu ...

** Demographic statistics * Dendrogram *

Density estimation In statistics, probability density estimation or simply density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of ...

* Dependent and independent variables *

Descriptive research Descriptive research is used to describe characteristics of a population or phenomenon being studied. It does not answer questions about how/when/why the characteristics occurred. Rather it addresses the "what" question (what are the characterist ...

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

Design effect In survey methodology, the design effect (generally denoted as D_ or D_^2) is a measure of the expected impact of a sampling design on the variance of an estimator for some parameter. It is calculated as the ratio of the variance of an estimator b ...

Design matrix In statistics and in particular in regression analysis, a design matrix, also known as model matrix or regressor matrix and often denoted by X, is a matrix of values of explanatory variables of a set of objects. Each row represents an individual ob ...

*Design of experiments **The Design of Experiments (book by Fisher) *Detailed balance *Detection theory *Determining the number of clusters in a data set *Detrended correspondence analysis *Detrended fluctuation analysis *Deviance (statistics) *Deviance information criterion *Deviation (statistics) *Deviation analysis (disambiguation) *DFFITS a regression diagnostic *Diagnostic odds ratio *Dickey–Fuller test *Difference in differences *Differential entropy *Diffusion process *Diffusion-limited aggregation *Dimension reduction *Dilution assay *Direct relationship *

*Dirichlet distribution *Dirichlet-multinomial distribution *Dirichlet process *Disattenuation *Discrepancy function *Discrete choice *Discrete choice analysis *Discrete distribution redirects to section of Probability distribution *Discrete frequency domain *Discrete phase-type distribution *Discrete probability distribution redirects to section of Probability distribution *Discrete time *Discretization of continuous features *Discriminant function analysis *Discriminative model *Disorder problem *Distance correlation *Distance sampling *Distributed lag *Distribution fitting *Divergence (statistics) *Diversity index *Divisia index *Divisia monetary aggregates index *Dixon's Q test *Dominating decision rule *Donsker's theorem *Doob decomposition theorem *Doob martingale *Doob's martingale convergence theorems *Doob's martingale inequality *Doob–Meyer decomposition theorem *Doomsday argument *Dot plot (bioinformatics) *Dot plot (statistics) *Double counting (fallacy) *Double descent *Double exponential distribution (disambiguation) *Double mass analysis *Doubly stochastic model *Drift rate redirects to Stochastic drift *Dudley's theorem *Dummy variable (statistics) *Duncan's new multiple range test *Dunn index *Dunnett's test *Durbin test *Durbin–Watson statistic *Dutch book *Dvoretzky–Kiefer–Wolfowitz inequality *Dyadic distribution *Dynamic Bayesian network *Dynamic factor *Dynamic topic model

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*E-statistic *Earth mover's distance *Eaton's inequality *Ecological correlation *Ecological fallacy *Ecological regression *Ecological study *Econometrics *Econometric model *Econometric software redirects to

*Economic data *Economic epidemiology *Economic statistics *Eddy covariance *Edgeworth series *Effect size *

*Efficient estimator *Ehrenfest model *Elastic map *Elliptical distribution *Ellsberg paradox *Elston–Stewart algorithm *EMG distribution *Empirical *Empirical Bayes method *Empirical distribution function *Empirical likelihood *Empirical measure *Empirical orthogonal functions *Empirical probability *Empirical process *Empirical statistical laws *Endogeneity (econometrics) *End point of clinical trials *Energy distance *Energy statistics (disambiguation) *Encyclopedia of Statistical Sciences (book) *Engineering statistics *Engineering tolerance *Engset calculation *Ensemble forecasting *Ensemble Kalman filter *Entropy (information theory) *Entropy estimation *Entropy power inequality *Environmental statistics *Epi Info software *Epidata software *Epidemic model *Epidemiological methods *Epilogism *Epitome (image processing) *Epps effect *Equating test equating *Equipossible *Equiprobable *Erdős–Rényi model *Erlang distribution *Ergodic theory *Ergodicity *Error bar *Error correction model *Error function *Errors and residuals in statistics *Errors-in-variables models *An Essay towards solving a Problem in the Doctrine of Chances *Estimating equations *Estimation theory *Estimation of covariance matrices *Estimation of signal parameters via rotational invariance techniques *Estimator *Etemadi's inequality *Ethical problems using children in clinical trials *Event (probability theory) *Event study *Evidence lower bound *

*Evolutionary data mining *Ewens's sampling formula *EWMA chart *Exact statistics *Exact test *Examples of Markov chains *Excess risk *Exchange paradox *Exchangeable random variables *Expander walk sampling *Expectation–maximization algorithm *Expectation propagation *Expected mean squares *Expected utility hypothesis *Expected value *Expected value of sample information *Experiment *Experimental design diagram *Experimental event rate *Experimental uncertainty analysis *Experimenter's bias *Experimentwise error rate *Explained sum of squares *Explained variation *Explanatory variable *Exploratory data analysis *Exploratory factor analysis *Exponential dispersion model *Exponential distribution *Exponential family *Exponential-logarithmic distribution *Exponential power distribution redirects to Generalized normal distribution *Exponential random numbers redirect to subsection of Exponential distribution *Exponential smoothing *Exponentially modified Gaussian distribution *Exponentiated Weibull distribution *Exposure variable *Extended Kalman filter *Extended negative binomial distribution *Extensions of Fisher's method *External validity *Extrapolation domain analysis *Extreme value theory *Extremum estimator

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*F-distribution *F-divergence *F-statistics population genetics *F-test *F-test of equality of variances *F1 score *Facet theory *Factor analysis *Factor regression model *Factor graph *Factorial code *Factorial experiment *Factorial moment *Factorial moment generating function *Failure rate *Fair coin *Falconer's formula *False discovery rate *False nearest neighbor algorithm *Type I and type II errors, False negative *Type I and type II errors, False positive *False positive rate *False positive paradox *Family-wise error rate *Fan chart (time series) *Fano factor *Fast Fourier transform *Fast Kalman filter *FastICA fast independent component analysis *Fat-tailed distribution *Feasible generalized least squares *Feature extraction *Feller process *Feller's coin-tossing constants *Feller-continuous process *Felsenstein's tree-pruning algorithm statistical genetics *Fides (reliability) *Fiducial inference *Field experiment *Fieller's theorem *File drawer problem *Filtering problem (stochastic processes) *Financial econometrics *Financial models with long-tailed distributions and volatility clustering *Finite-dimensional distribution *First-hitting-time model *First-in-man study *Fishburn–Shepp inequality *Fisher consistency *Fisher information *Fisher information metric *Fisher kernel *Fisher transformation *Fisher's exact test *Fisher's inequality *Fisher's linear discriminator *Fisher's method *Fisher's noncentral hypergeometric distribution *Fisher's z-distribution *Fisher–Tippett distribution redirects to Generalized extreme value distribution *Fisher–Tippett–Gnedenko theorem *Five-number summary *Fixed effects estimator and Fixed effects estimation redirect to Fixed effects model *Fixed-effect Poisson model *FLAME clustering *Fleiss' kappa *Fleming–Viot process *Flood risk assessment *Floor effect *Focused information criterion *Fokker–Planck equation *Folded normal distribution *Forecast bias *Forecast error *Forecast skill *Forecasting *Forest plot *Fork-join queue *Formation matrix *Forward measure *Foster's theorem *Foundations of statistics *Founders of statistics *Fourier analysis *Fowlkes–Mallows index *Fraction of variance unexplained *Fractional Brownian motion *Fractional factorial design *Fréchet distribution *Fréchet mean *Free statistical software *Freedman's paradox *Freedman–Diaconis rule *Freidlin–Wentzell theorem *Frequency (statistics) *Frequency distribution *Frequency domain *Frequency probability *Frequentist inference *Friedman test *Friendship paradox *Frisch–Waugh–Lovell theorem *Fully crossed design *Function approximation *Functional boxplot *Functional data analysis *Funnel plot *Fuzzy logic *Fuzzy measure theory *FWL theorem relating regression and projection

G

*G/G/1 queue *G-network *G-test *Galbraith plot *Gallagher Index *Galton–Watson process *Galton's problem *Gambler's fallacy *Gambler's ruin *Gambling and information theory *Game of chance *Gamma distribution *Gamma test (statistics) *Gamma process *Gamma variate *GAUSS (software) *Gauss's inequality *Gauss–Kuzmin distribution *Gauss–Markov process *Gauss–Markov theorem *Gauss–Newton algorithm *Gaussian function *Gaussian isoperimetric inequality *Gaussian measure *Gaussian noise *Gaussian process *Gaussian process emulator *Gaussian q-distribution *Geary's C *GEH statistic – a statistic comparing modelled and observed counts *General linear model *Generalizability theory *Generalized additive model *Generalized additive model for location, scale and shape *Generalized beta distribution *Generalized canonical correlation *Generalized chi-squared distribution *Generalized Dirichlet distribution *Generalized entropy index *Generalized estimating equation *Generalized expected utility *Generalized extreme value distribution *Generalized gamma distribution *Generalized Gaussian distribution *Generalised hyperbolic distribution *Generalized inverse Gaussian distribution *Generalized least squares *Generalized linear array model *Generalized linear mixed model *Generalized linear model *Generalized logistic distribution *Generalized method of moments *Generalized multidimensional scaling *Generalized multivariate log-gamma distribution *Generalized normal distribution *Generalized p-value *Generalized Pareto distribution *Generalized Procrustes analysis *Generalized randomized block design *Generalized Tobit *Generalized Wiener process *Generative model *Genetic epidemiology *GenStat software *Geo-imputation *Geodemographic segmentation *Geometric Brownian motion *Geometric data analysis *Geometric distribution *Geometric median *Geometric standard deviation *Geometric stable distribution *Geospatial predictive modeling *Geostatistics *German tank problem *Gerschenkron effect *Gibbs sampling *Gillespie algorithm *Gini coefficient *Girsanov theorem *Gittins index *GLIM (software) software *Glivenko–Cantelli theorem *GLUE (uncertainty assessment) *Goldfeld–Quandt test *Gompertz distribution *Gompertz function *Gompertz–Makeham law of mortality *Good–Turing frequency estimation *Goodhart's law *Goodman and Kruskal's gamma *Goodman and Kruskal's lambda *Goodness of fit *Gordon–Newell network *Gordon–Newell theorem *Graeco-Latin square *Grand mean *Granger causality *Graph cuts in computer vision a potential application of Bayesian analysis *Graphical model *Graphical models for protein structure *GraphPad InStat software *GraphPad Prism software *Gravity model of trade *Greenwood statistic *Gretl *Group family *Group method of data handling *Group size measures *Grouped data *Grubbs's test for outliers *Guess value *Guesstimate *Gumbel distribution *Guttman scale *Gy's sampling theory

H

*h-index *Hájek–Le Cam convolution theorem *Half circle distribution *Half-logistic distribution *Half-normal distribution *Halton sequence *Hamburger moment problem *Hannan–Quinn information criterion *Harris chain *Hardy–Weinberg principle statistical genetics *Hartley's test *Hat matrix *Hammersley–Clifford theorem *Hausdorff moment problem *Hausman specification test redirects to Hausman test *Haybittle–Peto boundary *Hazard function redirects to Failure rate *Hazard ratio *Heaps' law *Health care analytics *Heart rate variability *Heavy-tailed distribution *Heckman correction *Hedonic regression *Hellin's law *Hellinger distance *Helmert–Wolf blocking *Herdan's law *Herfindahl index *Heston model *Heteroscedasticity *Heteroscedasticity-consistent standard errors *Heteroskedasticity – see Heteroscedasticity *Hidden Markov model *Hidden Markov random field *Hidden semi-Markov model *Hierarchical Bayes model *Hierarchical clustering *Hierarchical hidden Markov model *Hierarchical linear modeling *High-dimensional statistics *Higher-order factor analysis *Higher-order statistics *Hirschman uncertainty *Histogram *Historiometry *History of randomness *History of statistics *Hitting time *Hodges' estimator *Hodges–Lehmann estimator *Hoeffding's independence test *Hoeffding's lemma *Hoeffding's inequality *Holm–Bonferroni method *Holtsmark distribution *Homogeneity (statistics) *Homogenization (climate) *Homoscedasticity *Hoover index (a.k.a. Robin Hood index) *Horvitz–Thompson estimator *Hosmer–Lemeshow test *Hotelling's T-squared distribution *How to Lie with Statistics (book) *Howland will forgery trial *Hubbert curve *Huber–White standard error – see Heteroscedasticity-consistent standard errors *Huber loss function *Human subject research *Hurst exponent *Hyper-exponential distribution *Hyper-Graeco-Latin square design *Hyperbolic distribution *Hyperbolic secant distribution *Hypergeometric distribution *Hyperparameter *Hyperprior *Hypoexponential distribution

I

*Idealised population *Idempotent matrix *Identifiability *Ignorability *

*Image denoising *Importance sampling *Imprecise probability *Impulse response *Imputation (statistics) *Incidence (epidemiology) *Increasing process *Indecomposable distribution *Independence of irrelevant alternatives *Independent component analysis *Independent and identically distributed random variables *Index (economics) *Index number *Index of coincidence *Index of dispersion *Index of dissimilarity *Indicators of spatial association *Indirect least squares *Inductive inference *An inequality on location and scale parameters – see

*Inference *Inferential statistics redirects to Statistical inference *Infinite divisibility (probability) *Infinite monkey theorem *Influence diagram *Info-gap decision theory *Information bottleneck method *Information geometry *Information gain ratio *Information ratio finance *Information source (mathematics) *Information theory *Inherent bias *Inherent zero *Injury prevention application *Innovation (signal processing) *Innovations vector *Institutional review board *Instrumental variable *Integrated nested Laplace approximations *Intention to treat analysis *Interaction (statistics) *Interaction variable see Interaction (statistics) *Interclass correlation *Interdecile range *Interim analysis *Internal consistency *Internal validity *Interquartile mean *Interquartile range *Inter-rater reliability *Interval estimation *Intervening variable *Intra-rater reliability *Intraclass correlation *Invariant estimator *Invariant extended Kalman filter *Inverse distance weighting *Inverse distribution *Inverse Gaussian distribution *Inverse matrix gamma distribution *Inverse Mills ratio *Inverse probability *Inverse probability weighting *Inverse relationship *Inverse-chi-squared distribution *Inverse-gamma distribution *Inverse transform sampling *Inverse-variance weighting *Inverse-Wishart distribution *Iris flower data set *Irwin–Hall distribution *Isomap *Isotonic regression *Isserlis' theorem *Item response theory *Item-total correlation *Item tree analysis *Iterative proportional fitting *Iteratively reweighted least squares *Itô calculus *Itô isometry *Itô's lemma

J

*Jaccard index *Jackknife (statistics) redirects to Resampling (statistics) *Jackson network *Jackson's theorem (queueing theory) *Jadad scale *James–Stein estimator *Jarque–Bera test *Jeffreys prior *Jensen's inequality *Jensen–Shannon divergence *JMulTi software *Johansen test *Johnson SU distribution *Joint probability distribution *Jonckheere's trend test *JMP (statistical software) *Jump process *Jump-diffusion model *Junction tree algorithm

K

*K-distribution *K-means algorithm redirects to k-means clustering *K-means++ *K-medians clustering *K-medoids *K-statistic *Kalman filter *Kaniadakis distribution *Kaniadakis statistics *Kaplan–Meier estimator *Kappa coefficient *Kappa statistic *Karhunen–Loève theorem *Kendall tau distance *Kendall tau rank correlation coefficient *Kendall's notation *Kendall's W Kendall's coefficient of concordance *Kent distribution *Kernel density estimation *Kernel Fisher discriminant analysis *Kernel methods *Kernel principal component analysis *Kernel regression *Kernel smoother *Kernel (statistics) *Khmaladze transformation (probability theory) *Killed process *Khintchine inequality *Kingman's formula *Kirkwood approximation *Kish grid *Kitchen sink regression *Klecka's tau *Knightian uncertainty *Kolmogorov backward equation *Kolmogorov continuity theorem *Kolmogorov extension theorem *Kolmogorov's criterion *Kolmogorov's generalized criterion *Kolmogorov's inequality *Kolmogorov's zero–one law *Kolmogorov–Smirnov test *KPSS test *Kriging *Kruskal–Wallis one-way analysis of variance *Kuder–Richardson Formula 20 *Kuiper's test *Kullback's inequality *Kullback–Leibler divergence *Kumaraswamy distribution *Kurtosis *Kushner equation

L

*L-estimator *L-moment *Labour Force Survey *Lack-of-fit sum of squares *Lady tasting tea *Lag operator *Lag windowing *Lambda distribution (disambiguation), Lambda distribution disambiguation *Landau distribution *Lander–Green algorithm *Language model *Laplace distribution *Laplace principle (large deviations theory) *LaplacesDemon software *Large deviations theory *Large deviations of Gaussian random functions *LARS – see least-angle regression *Latent variable, latent variable model *Latent class model *Latent Dirichlet allocation *Latent growth modeling *Latent semantic analysis *Latin rectangle *Latin square *Latin hypercube sampling *Law (stochastic processes) *Law of averages *Law of comparative judgment *Law of large numbers *Law of the iterated logarithm *Law of the unconscious statistician *Law of total covariance *Law of total cumulance *Law of total expectation *Law of total probability *Law of total variance *Law of truly large numbers *Layered hidden Markov model *Le Cam's theorem *Lead time bias *Least absolute deviations *Least-angle regression *Least squares *Least-squares spectral analysis *Least squares support vector machine *Least trimmed squares *Learning theory (statistics) *Leftover hash-lemma *Lehmann–Scheffé theorem *Length time bias *Levene's test *Level of analysis *Level of measurement *Levenberg–Marquardt algorithm *Leverage (statistics) *Levey–Jennings chart redirects to Laboratory quality control *Lévy's convergence theorem *Lévy's continuity theorem *Lévy arcsine law *Lévy distribution *Lévy flight *Lévy process *Lewontin's Fallacy *Lexis diagram *Lexis ratio *Lies, damned lies, and statistics *Life expectancy *Life table *Lift (data mining) *Likelihood function *Likelihood principle *Likelihood-ratio test *Likelihood ratios in diagnostic testing *Likert scale *Lilliefors test *Limited dependent variable *Limiting density of discrete points *Lincoln index *Lindeberg's condition *Lindley equation *Lindley's paradox *Line chart *Line-intercept sampling *Linear classifier *Linear discriminant analysis *Linear least squares *Linear model *Linear prediction *Linear probability model *Linear regression *Linguistic demography *Linnik distribution redirects to Geometric stable distribution *LISREL proprietary statistical software package *List of basic statistics topics redirects to Outline of statistics *List of convolutions of probability distributions *List of graphical methods *List of information graphics software *List of probability topics *List of random number generators *List of scientific journals in statistics *List of statistical packages *List of statisticians *Listwise deletion *Little's law *Littlewood's law *Ljung–Box test *Local convex hull *Local independence *Local martingale *Local regression *Location estimation redirects to Location parameter *Location estimation in sensor networks *Location parameter *Location test *Location-scale family *Local asymptotic normality *Locality (statistics) *Loess curve redirects to Local regression *Log-Cauchy distribution *Log-Laplace distribution *Log-normal distribution *Log-linear analysis *Log-linear model *Log-linear modeling redirects to Poisson regression *Log-log plot *Log-logistic distribution *Logarithmic distribution *Logarithmic mean *Logistic distribution *Logistic function *Logistic regression *Logit *Logit analysis in marketing *Logit-normal distribution *Log-normal distribution *Logrank test *Lomax distribution *Long-range dependency *Long Tail *Long-tail traffic *Longitudinal study *Longstaff–Schwartz model *Lorenz curve *Loss function *Lot quality assurance sampling *Lotka's law *Low birth weight paradox *Lucia de Berk prob/stats related court case *Lukacs's proportion-sum independence theorem *Lumpability *Lusser's law *

M

*M/D/1 queue *M/G/1 queue *M/M/1 queue *M/M/c queue *M-estimator **Redescending M-estimator *M-separation *Mabinogion sheep problem *Machine learning *Mahalanobis distance *Main effect *Mallows's Cp, Mallows's ''C_p'' *MANCOVA *Manhattan plot *Mann–Whitney U *MANOVA *Mantel test *MAP estimator redirects to Maximum a posteriori estimation *Marchenko–Pastur distribution *Marcinkiewicz–Zygmund inequality *Marcum Q-function *Margin of error *Marginal conditional stochastic dominance *Marginal distribution *Marginal likelihood *Marginal model *Marginal variable redirects to Marginal distribution *Mark and recapture *Markov additive process *Markov blanket *Markov chain **Markov chain geostatistics **Markov chain mixing time *Markov chain Monte Carlo *Markov decision process *Markov information source *Markov kernel *Markov logic network *Markov model *Markov network *Markov process *Markov property *Markov random field *Markov renewal process *Markov's inequality *Markovian arrival processes *Marsaglia polar method *Martingale (probability theory) *Martingale difference sequence *Martingale representation theorem *Master equation *Matched filter *Matching pursuit *Matching (statistics) *Matérn covariance function *Mathematica – software *Mathematical biology *Mathematical modelling in epidemiology *Mathematical modelling of infectious disease *Mathematical statistics *Matthews correlation coefficient *Matrix gamma distribution *Matrix normal distribution *Matrix population models *Matrix t-distribution *Mauchly's sphericity test *Maximal ergodic theorem *Maximal information coefficient *Maximum a posteriori estimation *Maximum entropy classifier redirects to Logistic regression *Maximum-entropy Markov model *Maximum entropy method redirects to Principle of maximum entropy *Maximum entropy probability distribution *Maximum entropy spectral estimation *Maximum likelihood *Maximum likelihood sequence estimation *Maximum parsimony *Maximum spacing estimation *Maxwell speed distribution *Maxwell–Boltzmann distribution *Maxwell's theorem *Mazziotta–Pareto index *MCAR (missing completely at random) *McCullagh's parametrization of the Cauchy distributions *McDiarmid's inequality *McDonald–Kreitman test statistical genetics *McKay's approximation for the coefficient of variation *McNemar's test *Meadow's law *Mean *Mean see also expected value *Mean absolute error *Mean absolute percentage error *Mean absolute scaled error *Mean and predicted response *Mean deviation (disambiguation) *Mean absolute difference, Mean difference *Mean integrated squared error *Mean of circular quantities *Mean percentage error *Mean preserving spread *Mean reciprocal rank *Mean signed difference *Mean square quantization error *Mean square weighted deviation *Mean squared error *Mean squared prediction error *Mean time between failures *Mean-reverting process redirects to Ornstein–Uhlenbeck process *Mean value analysis *Measurement, level of – see level of measurement. *Measurement invariance *MedCalc software *Median *Median absolute deviation *Median polish *Median test *Mediation (statistics) *Medical statistics *Medoid *Memorylessness *Mendelian randomization *Meta-analysis *Meta-regression *Metalog distribution *Method of moments (statistics) *Method of simulated moments *Method of support *Metropolis–Hastings algorithm *Mexican paradox *Microdata (statistics) *Midhinge *Mid-range *MinHash *Minimax *Minimax estimator *Minimisation (clinical trials) *Minimum chi-square estimation *Minimum distance estimation *Minimum mean square error *Minimum-variance unbiased estimator *Minimum viable population *Minitab *MINQUE minimum norm quadratic unbiased estimation *Misleading graph *Missing completely at random *Missing data *Missing values – see Missing data *Mittag–Leffler distribution *Mixed logit *Misuse of statistics *Mixed data sampling *Mixed-design analysis of variance *Mixed model *Mixing (mathematics) *Mixture distribution *Mixture model *Mixture (probability) *MLwiN *Mode (statistics) *Model output statistics *Model selection *Model specification *Moderator variable redirects to Moderation (statistics) *Modifiable areal unit problem *Moffat distribution *Moment (mathematics) *Moment-generating function *Moments, method of see method of moments (statistics) *Moment problem *Monotone likelihood ratio *Monte Carlo integration *Monte Carlo method *Monte Carlo method for photon transport *Monte Carlo methods for option pricing *Monte Carlo methods in finance *Monte Carlo molecular modeling *Moral graph *Moran process *Moran's I, Moran's ''I'' *Morisita's overlap index *Morris method *Mortality rate *Most probable number *Moving average *Moving-average model *Moving average representation redirects to Wold's theorem *Moving least squares *Multi-armed bandit *Multi-vari chart *Multiclass classification *Multiclass LDA (linear discriminant analysis) redirects to Linear discriminant analysis *Multicollinearity *Multidimensional analysis *Multidimensional Chebyshev's inequality *Multidimensional panel data *Multidimensional scaling *Multifactor design of experiments software *Multifactor dimensionality reduction *Multilevel model *Multilinear principal component analysis *Multinomial distribution *Multinomial logistic regression *Multinomial logit – see Multinomial logistic regression *Multinomial probit *Multinomial test *Multiple baseline design *Multiple comparisons *Multiple correlation *Multiple correspondence analysis *Multiple discriminant analysis *Multiple-indicator kriging *Multiple Indicator Cluster Survey *Multiple of the median *Multiple testing correction redirects to Multiple comparisons *Multiple-try Metropolis *Multiresolution analysis *Multiscale decision making *Multiscale geometric analysis *Multistage testing *Multitaper *Multitrait-multimethod matrix *Multivariate adaptive regression splines *Multivariate analysis *Multivariate analysis of variance *Multivariate distribution – see Joint probability distribution *Multivariate kernel density estimation *Multivariate normal distribution *Multivariate Pareto distribution *Multivariate Pólya distribution *Multivariate probit redirects to Multivariate probit model *Multivariate random variable *Multivariate stable distribution *Multivariate statistics *Multivariate Student distribution redirects to Multivariate t-distribution *Multivariate t-distribution

N

*n = 1 fallacy, ''n'' = 1 fallacy *N of 1 trial *Naive Bayes classifier *Nakagami distribution *List of national and international statistical services, National and international statistical services *Nash–Sutcliffe model efficiency coefficient *National Health Interview Survey *Natural experiment *Natural exponential family *Natural process variation *NCSS (statistical software) *Nearest-neighbor chain algorithm *Negative binomial distribution *Negative multinomial distribution *Negative predictive value *Negative relationship *Negentropy *Neighbourhood components analysis *Neighbor joining *Nelson rules *Nelson–Aalen estimator *Nemenyi test *Nested case-control study *Nested sampling algorithm *Network probability matrix *Neural network *Neutral vector *Newcastle–Ottawa scale *Newey–West estimator *Newman–Keuls method *Neyer d-optimal test *Neyman construction *Neyman–Pearson lemma *Nicholson–Bailey model *Nominal category *Noncentral beta distribution *Noncentral chi distribution *Noncentral chi-squared distribution *Noncentral F-distribution *Noncentral hypergeometric distributions *Noncentral t-distribution *Noncentrality parameter *Nonlinear autoregressive exogenous model *Nonlinear dimensionality reduction *Non-linear iterative partial least squares *Nonlinear regression *Non-homogeneous Poisson process *Non-linear least squares *Non-negative matrix factorization *Nonparametric skew *Non-parametric statistics *Non-response bias *Non-sampling error *Nonparametric regression *Nonprobability sampling *Normal curve equivalent *Normal distribution *Normal probability plot see also rankit *Normal score see also rankit and Z score *Normal variance-mean mixture *Normal-exponential-gamma distribution *Normal-gamma distribution *Normal-inverse Gaussian distribution *Normal-scaled inverse gamma distribution *Normality test *Normalization (statistics) *Normally distributed and uncorrelated does not imply independent *Notation in probability and statistics *Novikov's condition *np-chart *Null distribution *Null hypothesis *Null result *Nuisance parameter *Nuisance variable *Numerical data *Numerical methods for linear least squares *Numerical parameter redirects to statistical parameter *Numerical smoothing and differentiation *Nuremberg Code

O

*Observable variable *Observational equivalence *Observational error *Observational study *Observed information *Occupancy frequency distribution *Odds *Odds algorithm *Odds ratio *Official statistics *Ogden tables *Ogive (statistics) *Omitted-variable bias *Omnibus test *One- and two-tailed tests *One-class classification *One-factor-at-a-time method *One-tailed test redirects to One- and two-tailed tests *One-way analysis of variance *Online NMF Online Non-negative Matrix Factorisation *Open-label trial *OpenEpi software *OpenBUGS software *Operational confound *Operational sex ratio *Operations research *Opinion poll *Optimal decision *Optimal design *Optimal discriminant analysis *Optimal matching *Optimal stopping *Optimality criterion *Optimistic knowledge gradient *Optional stopping theorem *Order of a kernel *Order of integration *Order statistic *Ordered logit *Ordered probit *Ordered subset expectation maximization *Ordinal regression *Ordinary least squares *Ordination (statistics) *Ornstein–Uhlenbeck process *Orthogonal array testing *Orthogonality *Orthogonality principle *Outlier *Outliers in statistics redirects to Robust statistics (section) *Outliers ratio *Outline of probability *Outline of regression analysis *Outline of statistics *Overdispersion *Overfitting *Owen's T function *OxMetrics software

P

*p-chart *p-rep *P-value *P–P plot *Page's trend test *Paid survey *Paired comparison analysis *Paired difference test *Pairwise comparison *Pairwise independence *Panel analysis *Panel data *Panjer recursion a class of discrete compound distributions *Paley–Zygmund inequality *Parabolic fractal distribution *PARAFAC (parallel factor analysis) *Parallel coordinates – graphical display of data *Parallel factor analysis redirects to PARAFAC *Paradigm (experimental) *Parameter identification problem *Parameter space *Parametric family *Parametric model *Parametric statistics *Pareto analysis *Pareto chart *Pareto distribution *Pareto index *Pareto interpolation *Pareto principle *Park test *Partial autocorrelation redirects to Partial autocorrelation function *Partial autocorrelation function *Partial correlation *Partial least squares *Partial least squares regression *Partial leverage *Partial regression plot *Partial residual plot *Particle filter *Partition of sums of squares *Parzen window *Path analysis (statistics) *Path coefficient *Path space (disambiguation) *Pattern recognition *Pearson's chi-squared test (one of various chi-squared tests) *Pearson distribution *Pearson product-moment correlation coefficient *Pedometric mapping *People v. Collins (prob/stats related court case) *Per capita *Per-comparison error rate *Per-protocol analysis *Percentile *Percentile rank *Periodic variation redirects to Seasonality *Periodogram *Peirce's criterion *Pensim2 an econometric model *Percentage point *Permutation test redirects to Resampling (statistics) *Pharmaceutical statistics *Phase dispersion minimization *Phase-type distribution *Phi coefficient *Phillips–Perron test *Philosophy of probability *Philosophy of statistics *Pickands–Balkema–de Haan theorem *Pie chart *Piecewise-deterministic Markov process *Pignistic probability *Pinsker's inequality *Pitman closeness criterion *Pitman–Koopman–Darmois theorem *Pitman–Yor process *Pivotal quantity *Placebo-controlled study *Plackett–Burman design *Plate notation *Plot (graphics) *Pocock boundary *Poincaré plot *Point-biserial correlation coefficient *Point estimation *Point pattern analysis *Point process *Poisson binomial distribution *Poisson distribution *Poisson hidden Markov model *Poisson limit theorem *Poisson process *Poisson regression *Poisson random numbers redirects to section of Poisson distribution *Poisson sampling * Polar distribution – see

*Policy capturing *Political forecasting *Pollaczek–Khinchine formula *Pollyanna Creep *Polykay *Poly-Weibull distribution *Polychoric correlation *Polynomial and rational function modeling *Polynomial chaos *Polynomial regression *Polytree (Bayesian networks) *Pooled standard deviation redirects to Pooled variance *Pooling design *Popoviciu's inequality on variances *Statistical population, Population *Population dynamics *Population ecology application *Population modeling *Population process *Population pyramid *Population statistics *Population variance *Population viability analysis *Portmanteau test *Positive predictive value *Post-hoc analysis *Posterior predictive distribution *Posterior probability *Power law *

*Prais–Winsten estimation *Pre- and post-test probability *Precision (statistics) *Precision and recall *Prediction interval *Predictive analytics *Predictive inference *Predictive informatics *Predictive intake modelling *Predictive modelling *Predictive validity *Preference regression (in marketing) *Preferential attachment process – see Preferential attachment *PRESS statistic *Prevalence *Principal component analysis **Multilinear principal-component analysis *Principal component regression *Principal geodesic analysis *Principal stratification *Principle of indifference *Principle of marginality *Principle of maximum entropy *Prior knowledge for pattern recognition *Prior probability *Prior probability distribution redirects to Prior probability *Probabilistic causation *Probabilistic design *Probabilistic forecasting *Probabilistic latent semantic analysis *Probabilistic metric space *Probabilistic proposition *Probabilistic relational model *Probability *Probability bounds analysis *Probability box *Probability density function *Probability distribution *Probability density function, Probability distribution function (disambiguation) *Probability integral transform *Probability interpretations *Probability mass function *Probability matching *Probability metric *Probability of error *Probability of precipitation *Probability plot (disambiguation), Probability plot *Probability plot correlation coefficient redirects to Q–Q plot *Probability plot correlation coefficient plot *Probability space *Probability theory *Probability-generating function *Probable error *Probit *Probit model *Procedural confound *Process control *Process Window Index *Procrustes analysis *Proebsting's paradox *Product distribution *Product form solution *Profile likelihood redirects to Likelihood function *Progressively measurable process *Prognostics *Projection pursuit *Projection pursuit regression *Proof of Stein's example *Propagation of uncertainty *Propensity probability *Propensity score *Propensity score matching *Proper linear model *Proportional hazards models *Proportional reduction in loss *Prosecutor's fallacy *Proxy (statistics) *Psephology *Pseudo-determinant *Pseudo-random number sampling *Pseudocount *Pseudolikelihood *Pseudomedian *Pseudoreplication *PSPP (free software) *Psychological statistics *Psychometrics *Pythagorean expectation

Q

*Q test *Q-exponential distribution *Q-function *Q-Gaussian distribution *Q–Q plot *Q-statistic *Quadrat *Quadrant count ratio *Quadratic classifier *Quadratic form (statistics) *Quadratic variation *Qualitative comparative analysis *Qualitative data *Qualitative variation *Quality control *Quantile *Quantile function *Quantile normalization *Quantile regression *Quantile-parameterized distribution *Quantitative marketing research *Quantitative psychological research *Quantitative research *Quantum (Statistical programming language) *Quartile *Quartile coefficient of dispersion *Quasi-birth–death process *Quasi-experiment *Quasi-experimental design – see Design of quasi-experiments *Quasi-likelihood *Quasi-maximum likelihood *Quasireversibility *Quasi-variance *Questionnaire *Queueing model *Queueing theory *Queuing delay *teletraffic queuing theory, Queuing theory in teletraffic engineering *Quota sampling

R

*R programming language – see R (programming language) *R v Adams (prob/stats related court case) *Radar chart *Rademacher distribution *Radial basis function network *Raikov's theorem *Raised cosine distribution *Ramaswami's formula *Ramsey RESET test the Ramsey Regression Equation Specification Error Test *

*Random assignment *Random compact set *Random data see randomness *Random effects estimation – see Random effects model *Random effects model *Random element *Random field *Random function *Random graph *Random matrix *Random measure *Random multinomial logit *Random naive Bayes *Random permutation statistics *Random regular graph *Random sample *Random sampling *Random sequence *Random variable *Random variate *Random walk *Random walk hypothesis *Randomization *Randomized block design *Randomized controlled trial *Randomized decision rule *Randomized experiment *Randomized response *Randomness *Randomness tests *Range (statistics) *Rank abundance curve *Rank correlation mainly links to two following **Spearman's rank correlation coefficient **Kendall tau rank correlation coefficient *Rank product *Rank-size distribution *Ranking *Rankit *Ranklet *RANSAC *Rao–Blackwell theorem *Rao-Blackwellisation – see Rao–Blackwell theorem *Rasch model **Polytomous Rasch model *Rasch model estimation *Ratio distribution *Ratio estimator *Rational quadratic covariance function *Rayleigh distribution *Rayleigh mixture distribution *Raw score *Realization (probability) *Recall bias *Receiver operating characteristic *Reciprocal distribution *Rectified Gaussian distribution *Recurrence period density entropy *Recurrence plot *Recurrence quantification analysis *Recursive Bayesian estimation *Recursive least squares *Recursive partitioning *Reduced form *Reference class problem *Reflected Brownian motion *Regenerative process *Regression analysis see also linear regression *Regression Analysis of Time Series proprietary software *Regression control chart *Regression diagnostic *Regression dilution *Regression discontinuity design *Regression estimation *Regression fallacy *Regression-kriging *Regression model validation *Regression toward the mean *Regret (decision theory) *Reification (statistics) *Rejection sampling *Relationships among probability distributions *Relative change and difference *Relative efficiency redirects to

*Relative index of inequality *Relative likelihood *Relative risk *Relative risk reduction *Relative standard deviation *Relative standard error redirects to Relative standard deviation *Relative variance redirects to Relative standard deviation *Relative survival *Relativistic Breit–Wigner distribution *Relevance vector machine *Reliability (statistics) *Reliability block diagram *Reliability engineering *Reliability theory *Reliability theory of aging and longevity *Rencontres numbers a discrete distribution *Renewal theory *Repeatability *Repeated measures design *Replication (statistics) *Representation validity *Reproducibility *Resampling (statistics) *Rescaled range *Resentful demoralization experimental design *Residual. See errors and residuals in statistics. *Residual sum of squares *Response bias *Response rate (survey) *Response surface methodology *Response variable *Restricted maximum likelihood *Restricted randomization *Reversible-jump Markov chain Monte Carlo *Reversible dynamics *Rind et al. controversy interpretations of paper involving meta-analysis *Rice distribution *Richardson–Lucy deconvolution *Ridge regression redirects to Tikhonov regularization *Ridit scoring *Risk adjusted mortality rate *Risk factor *Risk function *Risk perception *Risk theory *Risk–benefit analysis *Robbins lemma *Robust Bayesian analysis *Robust confidence intervals *Robust measures of scale *Robust regression *Robust statistics *Root mean square *Root-mean-square deviation *Root mean square deviation (bioinformatics) *Root mean square fluctuation *Ross's conjecture *Rossmo's formula *Rothamsted Experimental Station *Round robin test *Rubin causal model *Ruin theory *Rule of succession *Rule of three (medicine) *Run chart *RV coefficient

S

*S (programming language) *S-PLUS *Safety in numbers *Sally Clark (prob/stats related court case) *Sammon projection *Sample mean and covariance redirects to Sample mean and sample covariance *Sample mean and sample covariance *Sample maximum and minimum *Sample size determination *Sample space *Sample (statistics) *Sample-continuous process *Sampling (statistics) **Simple random sampling **Snowball sampling **Systematic sampling **Stratified sampling ** Cluster sampling **distance sampling **Multistage sampling **Nonprobability sampling **Slice sampling * Sampling bias *Sampling design *Sampling distribution *Sampling error *Sampling fraction *Sampling frame *Sampling probability *Sampling risk *Samuelson's inequality *Sargan test *SAS (software) *SAS language * SAS System – see SAS (software) *Savitzky–Golay smoothing filter *Sazonov's theorem *Saturated array *Scale analysis (statistics) *Scale parameter *Scaled-inverse-chi-squared distribution *Scaling pattern of occupancy *Scatter matrix *Scatter plot *Scatterplot smoothing *Scheffé's method *Scheirer–Ray–Hare test *Schilder's theorem *Schramm–Loewner evolution *Schuette–Nesbitt formula *Schwarz criterion *Score (statistics) *Score test *Scoring algorithm *Scoring rule *SCORUS *Scott's Pi *SDMX a standard for exchanging statistical data *Seasonal adjustment *Seasonality *Seasonal subseries plot *Seasonal variation *Seasonally adjusted annual rate *Second moment method *Secretary problem *Secular variation *Seed-based d mapping *Seemingly unrelated regressions *Seismic to simulation *Selection bias *Selective recruitment *Self-organizing map *Self-selection bias *Self-similar process *Segmented regression *Seismic inversion *Self-similarity matrix *Semantic mapping (statistics) *Semantic relatedness *Semantic similarity *Semi-Markov process *Semi-log graph *Semidefinite embedding *Semimartingale *Semiparametric model *Semiparametric regression *Semivariance *Sensitivity (tests) *Sensitivity analysis *Sensitivity and specificity *Sensitivity index *Separation test *Sequential analysis *Sequential estimation *Sequential Monte Carlo methods redirects to Particle filter *Sequential probability ratio test *Serial dependence *Seriation (archaeology) *SETAR (model) a time series model *Sethi model *Seven-number summary *Sexual dimorphism measures *Shannon–Hartley theorem *Shape of the distribution *Shape parameter *Shapiro–Wilk test *Sharpe ratio *SHAZAM (software) *Shewhart individuals control chart *Shifted Gompertz distribution *Shifted log-logistic distribution *Shifting baseline *Shrinkage (statistics) *Shrinkage estimator *Sichel distribution *Siegel–Tukey test *Sieve estimator *Sigma-algebra *SigmaStat software *Sign test *Signal-to-noise ratio *Signal-to-noise statistic *Significance analysis of microarrays *Silhouette (clustering) *Simfit software *Similarity matrix *Simon model *Simple linear regression *Simple moving average crossover *Simple random sample *Simpson's paradox *Simulated annealing *Simultaneous equation methods (econometrics) *Simultaneous equations model *Single equation methods (econometrics) *Single-linkage clustering *Singular distribution *Singular spectrum analysis *Sinusoidal model *Sinkov statistic *Size (statistics) *Skellam distribution *Skew normal distribution *Skewness *Skorokhod's representation theorem *Slash distribution *Slice sampling *Sliced inverse regression *Slutsky's theorem *Small area estimation *Smearing retransformation *Smoothing *Smoothing spline *Smoothness (probability theory) *Snowball sampling *Sobel test *Social network change detection *Social statistics *SOFA Statistics software *Soliton distribution redirects to Luby transform code *Somers' D *Sørensen similarity index *Spaghetti plot *Sparse binary polynomial hashing *Sparse PCA sparse principal components analysis *Sparsity-of-effects principle *Spatial analysis *Spatial dependence *Spatial descriptive statistics *Spatial distribution *Spatial econometrics *Spatial statistics redirects to Spatial analysis *Spatial variability *Spearman's rank correlation coefficient *Spearman–Brown prediction formula *Species discovery curve *Specification (regression) redirects to Statistical model specification *Specificity (tests) *Spectral clustering – (cluster analysis) *Spectral density *Spectral density estimation *Spectrum bias *Spectrum continuation analysis *Speed prior *Spherical design *Split normal distribution *SPRT redirects to Sequential probability ratio test *SPSS software *SPSS Clementine software (data mining) *Spurious relationship *Square root biased sampling *Squared deviations *St. Petersburg paradox *Stability (probability) *Stable distribution *Financial models with long-tailed distributions and volatility clustering, Stable and tempered stable distributions with volatility clustering – financial applications *Standard deviation *Standard error *Standard normal deviate *Standard normal table *Standard probability space *Standard score *Standardized coefficient *Standardized moment *Standardised mortality rate *Standardized mortality ratio *Standardized rate *Stanine *STAR model a time series model *Star plot redirects to Radar chart *Stata *State space representation *Statgraphics software *Static analysis *Stationary distribution *Stationary ergodic process *Stationary process *Stationary sequence *Stationary subspace analysis *Statistic *STATISTICA software *Statistical arbitrage *Statistical assembly *Statistical assumption *Statistical benchmarking *Statistical classification *Statistical conclusion validity *Statistical consultant *Statistical deviance – see deviance (statistics) *Statistical dispersion *Statistical distance *Statistical efficiency *Statistical epidemiology *Statistical estimation redirects to Estimation theory *Statistical finance *Statistical genetics redirects to population genetics *Statistical geography *Statistical graphics * Statistical hypothesis testing *Statistical independence *Statistical inference *Statistical interference *Statistical Lab software *Statistical learning theory *Statistical literacy *Statistical model *Statistical model specification *Statistical model validation *Statistical noise *List of statistical packages, Statistical package *Statistical parameter *Statistical parametric mapping *Statistical parsing *Statistical population *Statistical power *Statistical probability *Statistical process control *Statistical proof *Statistical randomness *Statistical range see range (statistics) *Statistical regularity *Statistical relational learning *Statistical sample *Statistical semantics *Statistical shape analysis *Statistical signal processing *Statistical significance *Statistical survey *Statistical syllogism *Statistical theory *Statistical unit *Statisticians' and engineers' cross-reference of statistical terms *Statistics *Statistics education *Statistics Online Computational Resource training materials *StatPlus *StatXact software *Stein's example **Proof of Stein's example *Stein's lemma *Stein's unbiased risk estimate *Steiner system *Stemplot – see Stem-and-leaf display *Step detection *Stepwise regression *Stieltjes moment problem *Stimulus-response model *Stochastic *Stochastic approximation *Stochastic calculus *Stochastic convergence *Stochastic differential equation *Stochastic dominance *Stochastic drift *Stochastic equicontinuity *Stochastic gradient descent *Stochastic grammar *Stochastic investment model *Stochastic kernel estimation *Stochastic matrix *Stochastic modelling (insurance) *Stochastic optimization *Stochastic ordering *Stochastic process *Stochastic rounding *Stochastic simulation *Stopped process *Stopping time *Stratified sampling *Stratonovich integral *Streamgraph *Stress majorization *Strong law of small numbers *Strong prior *Structural break *Structural equation modeling *Structural estimation *Structured data analysis (statistics) *Studentized range *Studentized residual *Student's t-distribution *Student's t-statistic *Student's t-test *Student's t-test for Gaussian scale mixture distributions – see Location testing for Gaussian scale mixture distributions *Studentization *Study design *Study heterogeneity *Subcontrary mean redirects to Harmonic mean *Subgroup analysis *Subindependence *Substitution model *SUDAAN software *Sufficiency (statistics) – see Sufficient statistic *Sufficient dimension reduction *Sufficient statistic *Sum of normally distributed random variables *Sum of squares (disambiguation) general disambiguation *Sum of squares (statistics) – see Partition of sums of squares *Summary statistic *Support curve *Support vector machine *Surrogate model *Survey data collection *Survey sampling *Survey methodology *Survival analysis *Survival rate *Survival function *Survivorship bias *Symmetric design *Symmetric mean absolute percentage error *SYSTAT (statistics), SYSTAT software *System dynamics *System identification *Systematic error (also see bias (statistics) and errors and residuals in statistics) *Systematic review

T

*t-distribution – see Student's t-distribution (includes table) *T distribution (disambiguation) *t-statistic *Tag cloud graphical display of info *Taguchi loss function *Taguchi methods *Tajima's D *Taleb distribution *Tampering (quality control) *Taylor expansions for the moments of functions of random variables *Taylor's law empirical variance-mean relations *Telegraph process *Test for structural change *Test–retest reliability *Test score *Test set *Test statistic *Testimator *Testing hypotheses suggested by the data *Text analytics *The Long Tail possibly seminal magazine article *The Unscrambler software *Theil index *Theil–Sen estimator *Theory of conjoint measurement *Therapeutic effect *Thompson sampling *Three-point estimation *Three-stage least squares *Threshold model *Thurstone scale *Thurstonian model *Time–frequency analysis *Time–frequency representation *Time reversibility *Time series *Time-series regression *Time use survey *Time-varying covariate *Timeline of probability and statistics *TinkerPlots proprietary software for schools *Tobit model *Tolerance interval *Top-coded *Topic model (statistical natural language processing) *Topological data analysis *Tornqvist index *Total correlation *Total least squares *Total sum of squares *Total survey error *Total variation distance of probability measures, Total variation distance a statistical distance measure *TPL Tables software *Tracy–Widom distribution *Traffic equations *Training set *Transect *Transferable belief model *Transiogram *Transition rate matrix *Transmission risks and rates *Treatment and control groups *Trend analysis *Trend estimation *Trend-stationary process *Treynor ratio *Triangular distribution *Trimean *Trimmed estimator *Trispectrum *True experiment *True variance *Truncated distribution *Truncated mean *Truncated normal distribution *Truncated regression model *Truncation (statistics) *Tsallis distribution *Tsallis statistics *Tschuprow's T *Tucker decomposition *Tukey's range test multiple comparisons *Tukey's test of additivity interaction in two-way anova *Tukey–Duckworth test *Tukey–Kramer method *Tukey lambda distribution *Tweedie distribution *Twisting properties *Two stage least squares redirects to Instrumental variable *Two-tailed test *Two-way analysis of variance *Type I and type II errors *Type-1 Gumbel distribution *Type-2 Gumbel distribution *Tyranny of averages

U

*u-chart *U-quadratic distribution *U-statistic *U test *Umbrella sampling *Unbiased estimator – see bias (statistics) *Unbiased estimation of standard deviation *Uncertainty *Uncertainty coefficient *Uncertainty quantification *Uncomfortable science *Uncorrelated *Underdispersion redirects to Overdispersion *Underfitting redirects to Overfitting *Underprivileged area score *Unevenly spaced time series * Unexplained variation – see Explained variation *Uniform distribution (continuous) *Uniform distribution (discrete) *Uniformly most powerful test *Unimodal distribution redirects to Unimodal function (has some stats context) *Unimodality *Unistat software *Unit (statistics) *Unit of observation *Unit root *Unit root test *Unit-weighted regression *Unitized risk *Univariate *Univariate analysis *Univariate distribution *Unmatched count *Unseen species problem *Unsolved problems in statistics *Upper and lower probabilities *Upside potential ratio finance *Urn problem *Ursell function *Utility maximization problem *Utilization distribution

V

*Validity (statistics) *Van der Waerden test *Van Houtum distribution *Vapnik–Chervonenkis theory *Varadhan's lemma *Variable (mathematics), Variable *Variable kernel density estimation *Variable-order Bayesian network *Variable-order Markov model *Variable rules analysis *Variance *Variance decomposition of forecast errors *Variance gamma process *Variance inflation factor *Variance-gamma distribution *Variance reduction *Variance-stabilizing transformation *Variance-to-mean ratio *Variation ratio *Variational Bayesian methods *Variational message passing *Variogram *Varimax rotation *Vasicek model *VC dimension *VC theory *Vector autoregression *VEGAS algorithm *Violin plot *ViSta – Software, see ViSta, The Visual Statistics system *Voigt profile *Volatility (finance) *Volcano plot (statistics) *Von Mises distribution *Von Mises–Fisher distribution *V-optimal histograms *V-statistic *Vuong's closeness test *Vysochanskiï–Petunin inequality

W

*Wait list control group *Wald distribution redirects to Inverse Gaussian distribution *Wald test *Wald–Wolfowitz runs test *Wallenius' noncentral hypergeometric distribution *Wang and Landau algorithm *Ward's method *Watterson estimator *Watts and Strogatz model *Weibull chart redirects to Weibull distribution *Weibull distribution *Weibull modulus *Weight function *Weighted median *Weighted covariance matrix redirects to Sample mean and sample covariance *Weighted mean *Weighted sample redirects to Sample mean and sample covariance *Welch's method spectral density estimation *Welch's t test *Welch–Satterthwaite equation *Well-behaved statistic *Wick product *Wilks' lambda distribution *Wilks' theorem redirects to section of Likelihood-ratio test *Winsorized mean *Whipple's index *White test *White noise *Wide and narrow data *Wiener deconvolution *Wiener filter *Wiener process *Wigner quasi-probability distribution *Wigner semicircle distribution *Wike's law of low odd primes *Wilcoxon signed-rank test *Will Rogers phenomenon *WinBUGS software *Window function *Winpepi software *Winsorising *Wishart distribution *Wold's theorem *Wombling *Working–Hotelling procedure *World Programming System software *Wrapped Cauchy distribution *Wrapped distribution *Wrapped exponential distribution *Wrapped normal distribution *Wrapped Lévy distribution *Writer invariant

X

*X-12-ARIMA *X-bar chart,

\bar x

chart *Xbar and R chart,

\bar x

and R chart *Xbar and s chart,

\bar x

and s chart *XLispStat software *XploRe software

Y

*Yamartino method *Yates analysis *Yates's correction for continuity *Youden's J statistic *Yule–Simon distribution

Z

*z-score *z-factor *z statistic *Z-test *Z-transform *Zakai equation *Zelen's design *Zero degrees of freedom *Zero–one law (disambiguation) *Zeta distribution *Ziggurat algorithm *Zipf–Mandelbrot law a discrete distribution *Zipf's law

External links

ISI Glossary of Statistical Terms
(multilingual), International Statistical Institute {{DEFAULTSORT:Statistics Statistics-related lists, Mathematics-related lists Indexes of business topics Lists of topics

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See also

External links