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.

Type to find tags:
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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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data observed over time (either in continuous time or at discrete time periods).
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Methods and principles of building "computer systems that automatically improve with experience."
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A probability provides a quantitative description of the likely occurrence of a particular event.
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Hypothesis testing assesses whether data support a given hypothesis rather than being an effect of random fluctuations or some other process described by an alternative hypothesis.
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A routine question from a textbook, course, or test used for a class or self-study. This community's policy is to "provide helpful hints" for self-study questions.
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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 measure of the degree of linear association among a pair of variables.
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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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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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a method of statistical inference that relies on turning the model parameters into random variables and applying Bayes' theorem to deduce probability statements about the paramet…
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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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The normal, or Gaussian, distribution has a density function that is a symmetrical bell-shaped curve. It is often used as a reference against which other distributions are compared.
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Partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. Clustered-standard-errors and/or cluster-samples should be t…
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Mathematical theory of statistics, concerned with formal definitions and general results.
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Regression that includes two or more non-constant independent variables.
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An interval of random variables, depending on observed data, which, with a fixed probability, contain an unknown parameter of interest.
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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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Categorical data can take on a limited (usually fixed) number of possible values called categories. Categorical values "label", they do not "measure". Nominal and dichotomous/binary scale types are ca…
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Any statistical process which seeks to approximate an unknown value, such as a distribution, a point estimate (e.g. mean), or confidence interval.
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Refers to a class of models developed to account for correlation that may occur within nested data.
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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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SPSS (Statistical Package for the Social Sciences) is a proprietary cross-platform general-purpose statistical software package.
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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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Creating samples from a well-specified population using a probabilistic method and/or producing random numbers from a specified distribution.
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Repeated measures data occurs when more than one measurement is collected on the same unit (e.g. subject). This data cannot be analysed through normal methods because the rows in the data are not inde…
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a technique to decompose an array of numerical data into a set of orthogonal vectors (uncorrelated linear combinations of the variables) called principal components. Th…
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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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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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Forecasting involves estimating the value or distribution of a random variable which has not yet been observed.
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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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Refers to general procedures that attempt to determine the generalizability of a statistical result. Cross-validation arises frequently in the context of assessing how a particular model fit predicts …
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Neural networks traditionally refer to a network or circuit of biological neurons. The modern usage of the term often refers to artificial neural networks (ANN), which are composed of artificial neuro…
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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.