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 vast area which includes generating results from computer models.
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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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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 dimensionality reduction latent variable technique which replaces inter-correlating variables by a smaller number of continuous latent variables called factors. The factors are be…
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The parameters of a regression model.
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Refers to the standard deviation of the sampling distribution of a statistic calculated from a sample. Standard errors are often required when forming confidence intervals or testing hypotheses about …
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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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Markov Chain Monte Carlo (MCMC) 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 tar…
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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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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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an observation that appears to be unusual or not well described relative to a simple characterization of a dataset. A discomfiting possibility is that these data come from a different po…
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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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collect a sample from a population. Surveying often refers to sampling of human populations and is primarily done by administering questionnaires or interviewing indivi…
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"Ordinal" data refers to data with values categorical yet underlying quantitative: the categories can be ordered by magnitude, but the exact magnitude of the spacing between them is undetermined. [Not…
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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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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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A binary variable takes one of two values, typically coded as "0" and "1".
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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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a formalization of relationships between variables in the form of mathematical equations. The model is statistical as the variables are not deterministically but stochastically …
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'Classification And Regression Trees'. CART is a popular data mining technique.
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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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Indicates questions asking about the use and meaning of specific technical words/concepts in statistics.
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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 very popular, semi-parametric method for survival analysis.
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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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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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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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A way of re-expressing data to make their values lie within a specified range.
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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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Using (pseudo-)random numbers and the Law of Large Numbers to simulate the random behavior of a real system.
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its deviation from the true value, which may be unobservable (e.g., regression parameters), or observable (e.g., future realizations). Use the [error-message]…
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Non-constant variance along some continuum in a random process.
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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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A regularization method for regression models that shrinks coefficients towards zero, making some of them equal to zero. Thus lasso performs feature selection.
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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 new area of Machine Learning research concerned with the technologies used for learning hierarchical representations of data, mainly done with deep neural networks (i.e. networks with two or more hi…