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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.

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Questions connected to R packages lme4 and nlme for linear, generalized linear and nonlinear mixed effects models. For general questions about mixed models use [mixed-model] tag.
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Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis."
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Refers to the AutoRegressive Integrated Moving Average model used in time series modeling both for data description and for forecasting. This model generalizes the ARMA model by including a term for d…
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a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or mo…
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for any use of optimization within statistics.
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Repeated measures data occur when more than one measurement is collected on the same unit (e.g. subject). Use this tag for RM-ANOVA together with [anova] tag.
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Questions seeking external references (books, papers, etc.) about a particular subject. Always use a more specific tag in addition.
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more than one response or dependent variable of interest. This can be contrasted with "multiple" or "multivariable" analysis, which typically implies more than one predictor or…
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In frequentist hypothesis testing, the $p$-value is the probability of a result as extreme (or more) than the observed result, under the assumption that the null hypothesis is true.
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Survival analysis models time to event data, typically time to death or failure time. Censored data are a common problem for survival analyses.
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Methods and principles of selecting a subset of attributes for use in further modelling
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Refers to a general estimation technique that selects the parameter value to minimize the squared difference between two quantities, such as the observed value of a variable, and the expected value of…
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Mathematical re-expression, often nonlinear, of data values. Data are often transformed either to meet the assumptions of a statistical model or to make the results of an analysis more interpretable.
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a machine-learning method based on combining the outputs of many decision trees.
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IBM SPSS Statistics (formerly SPSS, i.e. "Statistical Package for the Social Sciences") is a proprietary cross-platform general-purpose statistical software package. [For SPSS Modeler, use 'spss-model…
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The binomial distribution gives the frequencies of "successes" in a fixed number of independent "trials". Use this tag for questions about data that might be binomially distributed or for questions a…
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a field of statistics dealing with applications to economics.
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A situation where the effect of an explanatory variable may depend on the value of another explanatory variable.
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The expected value of a random variable; or a location measure for a sample.
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Drawing conclusions about population parameters from sample data. See https://en.wikipedia.org/wiki/Inference and https://en.wikipedia.org/wiki/Statistical_inference
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Refers to any model where a random variable is related to one or more random variables by a function that is linear in a finite number of parameters.
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a value that is subject to chance variation (i.e., randomness in a mathematical sense).
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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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Refers generally to making substantive conclusions from the results of a statistical analysis.
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The probability that an event A will occur, when another event B is known to occur or to have occurred. It is commonly denoted by P(A|B).
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Prediction of unknown random quantities, using a statistical model.
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the square root of the variance of a random variable, an estimator thereof, or a similar measure of the spread of a batch of data.
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off-topic on this site. Use this tag for questions concerning creating, processing, or maintaining datasets.
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a problem of judging which model from some set performs best. Popular methods include $R^2$, AIC and BIC criteria, test sets, and cross-validation. To some extent, feature selection…
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Procedures that rely on relatively few assumptions about underlying probability distributions.
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A discrete distribution defined on the non-negative integers that has the property that the mean is equal to the variance.
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a resampling method to estimate the sampling distribution of a statistic.
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The parameters of a regression model. Most commonly, the values by which the independent variables will be multiplied to get the predicted value of the dependent variable.
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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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very ambiguous. Use it when the question is about sample size and NONE of the following are more appropriate: [small-sample], [large-data], [power-analysis], [power], [underdetermined] or …
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concerned about achieving intended power and size when more than one hypothesis test is performed.