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Tags

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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for any *on-topic* question that (a) involves `R` either as a critical part of the question or expected answer, & (b) is not *just* about how to use `R`.
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Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
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Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervis…
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data observed over time (either in continuous time or at discrete time periods).
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A probability provides a quantitative description of the likely occurrence of a particular event.
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inconsistent with a given hypothesis rather than being an effect of random fluctuations.
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A routine exercise from a textbook, course, or test used for a class or self-study. This community's policy is to "provide helpful hints" for such questions rather than complete answers.
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a mathematical description of probabilities or frequencies.
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Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
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a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about t…
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the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of dat…
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composed of 'neurons' - programming constructs that mimic the properties of biological neurons. A set of weighted connections between the neurons allows informati…
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A measure of the degree of linear association among a pair of variables.
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Statistical significance refers to the probability that, if, in the population from which this sample were drawn the true effect were 0 (or some hypothesized value) a test statistic as extreme or more…
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Mathematical theory of statistics, concerned with formal definitions and general results.
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The normal, or Gaussian, distribution has a density function that is a symmetrical bell-shaped curve. It is one of the most important distributions in statistics. Use the [normality] tag for asking ab…
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ANOVA stands for ANalysis Of VAriance, a statistical model and set of procedures for comparing multiple group means. The independent variables in an ANOVA model are categorical, but an ANOVA table can…
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Regression that includes two or more non-constant independent variables.
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Mixed (aka multilevel or hierarchical) models are linear models that include both fixed effects and random effects. They are used to model longitudinal or nested data.
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the task of partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. [Clustered-standard-errors a…
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an interval that covers an unknown parameter with $(1-\alpha)\%$ confidence. Confidence intervals are a frequentist concept. They are often confused with credible intervals wh…
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A generalization of linear regression allowing for nonlinear relationships via a "link function" and for the variance of the response to depend on the predicted value. (Not to be confused with "genera…
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The expected squared deviation of a random variable from its mean; or, the average squared deviation of data about their mean.
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Categorical (also called nominal) data can take on a limited number of possible values called categories. Categorical values "label", they do not "measure". Please use [ordinal-data] tag for discrete …
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a special case of [prediction], in the context of [time-series].
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a linear dimensionality reduction technique. It reduces a multivariate dataset to a smaller set of constructed variables preserving as much information (as much v…
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a general purpose programming language designed for ease of use. It is a commonly used platform for machine learning. Use this tag for any *on-topic* question that (a) involves `Python` eith…
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too general; please provide a more specific tag. For questions about the properties of specific estimators, use [estimators] tag instead.
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Repeatedly withholding subsets of the data during model fitting in order to quantify the model performance on the withheld data subsets.
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A test for comparing the means of two samples, or the mean of one sample (or even parameter estimates) with a specified value; also known as the "Student t-test" after the pseudonym of its inventor.
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Constructing meaningful and useful graphical representations of data. (If your question is only about how to get particular software to produce a specific effect, then it is likely not on topic here.)
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An area of machine learning concerned with learning hierarchical representations of the data, mainly done with deep neural networks.
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a method of estimating parameters of a statistical model by choosing the parameter value that optimizes the probability of observing the given sample.
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Creating samples from a well-specified population using a probabilistic method and/or producing random numbers from a specified distribution. As this tag is ambiguous, please consider [survey-sampling…
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A test (typically of distribution, independence, or goodness of fit) or a family of distributions related to such a test.
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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.