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.

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a quantity used to measure the strength and direction of the linear relationship between two variables. The covariance is unscaled, & thus often difficult to interpret; when scaled by th…
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a proprietary cross-platform general-purpose statistical software package. [Official Website](http://www.sas.com/index.html)
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a value that is subject to chance variation (i.e., randomness in a mathematical sense).
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concerned with assessing the probability of unknown values from known values and inferred relationships.
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the correlation of a series of data with itself at some lag. This is an important topic particularly in the analysis of time-series data.
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When the data present lack of information (gaps), i.e., are not complete. Hence, it is important to consider this feature when performing a analysis or test.
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Markov Chain Monte Carlo refers to a class of methods for generating samples from a target distribution by generating random numbers from a Markov Chain whose stationary distribution is the target dis…
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Statistical methods appropriate for the analysis of data sets comprising several levels of hierarchy of units of analysis (e.g., students nested in classes nested in schools; observations nested in pa…
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a a set of one or more computations that will produce a calculated result. All statistics methods are algorithms. Algorithms can be simple, such as calculating a percentage, or can be …
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'ordinal` refers to data that have an order but not necessarily equal spacing between levels. It can also refer to ordinal logistic regression.
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an observation that appears to be unusual or not well described relative to a simple characterization of a dataset.
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PDF stands for Probability Density Function. The PDF of a variable gives the relative probability for each value of a continuous variable. Use this tag when asking about probability functions in gener…
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Inference, in a statistical context, refers to drawing conclusions from data containing an element of randomness introduced by e.g. measurement error, sampling variation, or assignment of experimental…
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a weighted average of all possible values a random variable can take on, with the weights equal to the probability of taking on that value.
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Goodness of fit tests indicate whether or not it is reasonable to assume that a random sample comes from a specific distribution.
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Panel data refers to multi-dimensional data frequently involving measurements over time in econometrics. It is also called longitudinal data in biostatistics.
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functions in the R package lme4 that fit mixed effects models (ie, models that include fixed & random effects). These models can be non-linear in the sense that the…
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only for regression models (q.v.) in which the response is a nonlinear functions of the *parameters* (not because it's a nonlinear function of the *predictors*).
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A stochastic process describes evolution of random variables/systems over time and/or space and/or any other index set. It has applications in areas such as econometrics, weather, signal processing, e…
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Parameters associated with the particular levels of a covariate are sometimes called the “effects” of the levels. If the levels that are observed represent a random sample from the set of all possible…
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The parameters of a regression model.
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the actual values minus the predicted values. Many statistical models make assumptions about the error, which is estimated by the residuals.
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Refers to a subset of data mining concerned with extracting information from data in the form of text by recognizing patterns. The goal of text mining is often to classify a given document into one of…
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the fraction of some total that is of a particular kind, either (i) as a count of one type of thing out of a total count, or (ii) as a component of a continuous variable.
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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.
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Using (pseudo-)random numbers to simulate the random behavior of a real system.
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a random process that has non-constant variance along some continuum.
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A way of re-expressing data to make their values lie between 0 and 1 (or 0% and 100%).
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Stands for 'Classification And Regression Trees'. CART is a technique for developing a tree model (T) to predict categories (C) and/or continuous values (R) by recursive partitioning. It does not make…
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A stochastic process with the property that the future is conditionally independent of the past, given the present.
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Classically, a Likert scale was composed of the sum of many Likert items (ordinal ratings of the amount of agreement with a statement), where all the items were equally valid. Today the term sometimes…
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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…
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Kernel refers to weighting functions used in non-parametric estimation techniques.
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the deviation of the observed value from the (unobservable) true function value. Do NOT use this tag for SOFTWARE ERROR messages.
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independent when information on some of them tells you nothing about the probability of occurrence (/ distribution) of the others. Please DO NOT use this tag for indep…
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A form of regularization used in the estimation of regression coefficients that shrinks coefficient estimates by penalizing their absolute value (i.e. the $L_1$ norm of the estimates). Some coefficien…