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A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.

A discrete, univariate distribution modelling the number of ${\rm Bernoulli}(p)$ trial successes until a specified number of failures occur.
Count data are non-negative integers representing whole amounts.
879 questions
Poisson regression is one of a number of regression models for dependent variables that are counts (non-negative integers). A more general model is negative binomial regression. Both have numerous var…
A matrix (plural matrices) is a rectangular array of numbers, symbols, or expressions arranged in rows and columns. The individual items in a matrix are called its elements or entries.
Effect size is "a measure of the strength of a phenomenon or a sample-based estimate of that quantity" [Wikipedia].
Receiver Operating Characteristic, also known as the ROC curve, is a graphical plot that illustrates the diagnostic ability of a binary classifier system
A model for time series in which the conditional variance is time-varying and autocorrelated.
A non-negative continuous probability distribution indexed by two strictly positive parameters.
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The process of assessing whether the results of an analysis are likely to hold outside of the original research setting. DO NOT use this tag for discussing 'validity' of a measurement or instrument (s…
The field of study concerning statistical methods that use space and spatial relationships (such as distance, area, volume, length, height, orientation, centrality and/or other spatial characteristics…
816 questions
The quantiles of a distribution refer to points on its cumulative distribution function. Some common quantiles are quartiles and percentiles.
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A conditional expectation is the expectation of a random variable, given information on another variable or variables (mostly, by specifying their value).
795 questions
Accuracy of an estimator is the degree of closeness of the estimates to the true value. For a classifier, accuracy is the proportion of correct classifications. (This second usage is not good practice…
A Long Short Term Memory (LSTM) is a neural network architecture that contains recurrent NN blocks that can remember a value for an arbitrary length of time.
The Wilcoxon rank sum test, also known as Mann-Whitney U test, is a non-parametric rank test to assess whether one of two samples has larger values than the other.
Joint probability distribution of several random variables gives the probability that all of them simultaneously lie in a particular region.
A multivariate, discrete probability distribution used to describe the results of a random experiment where each of $n$ outcomes are placed into one of $k$ nominal categories.
Vector Auto-Regression, a multivariate time-series model / method. Under VAR, each univariate time-series is a linear combination of its own previous values and the previous values of the other series…
Usually refers to "z-standardization" which is shifting and rescaling data to assure they have zero mean and unit variance. Other "standardizations" are possible, too.
The uniform distribution describes a random variable that is equally likely to take any value in its sample space.
762 questions
The process of fiting some statistical model to a particular set of data. Mostly done on a computer, and using varied numerical methods such as optimization or numerical integration, or simulation. …
A rule for calculating an estimate of a given quantity based on observed data [Wikipedia].
Representing categorical variables as sets of numerical variables. Necessary in many types of analysis for them to process categorical data. A common example is using a categorical predictor in regres…
For questions about the central limit theorem, which states: "Given certain conditions, the mean of a sufficiently large number of iterates of independent random variables, each with a well-defined me…
Seasonality refers to the recurring fluctuation around the mean of a time-series for a given period of time, usually a calendar year.
Asymptotic theory studies the properties of estimators and test statistics when the sample size approaches infinity.
A random variable $X$ is called continuous if its set of possible values is uncountable, and the chance that it takes any particular value is zero ($\text{P}(X = x) = 0$ for every real number $x$). A …
The act of generating a sequence of numbers or symbols randomly, or (almost always) pseudo-randomly; i.e., with lack of any predictability or pattern.
743 questions
Questions that seek a conceptual or non-mathematical understanding of statistics.
738 questions
Cumulative distribution function. While the PDF gives the probability density of each value of a random variable, the CDF (often denoted $F(x)$) gives the probability that the random variable will be …
Feature engineering is the process of using domain knowledge of the data to create features for machine learning models. This tag is meant for both theoretical and practical questions regarding featur…
A regularization method for regression models that shrinks coefficients towards zero.
A distribution describing the time between events in a Poisson process; a continuous analogue of the geometric distribution.
Refers to an estimator of a population parameter that "hits the true value" on average. That is, a function of the observed data $\hat{\theta}$ is an unbiased estimator of a parameter $\theta$ if $E(\…
Kernel methods are used in machine learning to generalize linear techniques to nonlinear situations, especially SVMs, PCA, and GPs. Not to be confused with [kernel-smoothing], for kernel density estim…
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