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A non-negative continuous probability distribution indexed by two strictly positive parameters.
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Shifting and rescaling data to assure zero mean and unit variance.
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Psychometrics has evolved as a subfield of psychology to become the science of measurement of unobservable individual characteristics.
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A discrete, univariate distribution modelling the number of ${\rm Bernoulli}(p)$ trial successes until a specified number of failures occur.
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collected repeatedly on the same subjects. When there is a long series of data, time series analysis may be appropriate. For shorter series, mixed models (a…
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Refers to data generated from a distribution that has a countable sample space. Discrete data may be nominal (e.g. the distribution of race in a sample of individuals) or ordinal (e.g. the number of e…
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the study of the distribution and spread of disease or illness at the population level.
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Average most often refers to the arithmetic mean, but more generally to measures of central tendency that use most, or all, of the data values. Examples include trimmed mean, Winsorized mean, harmonic…
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a simple probabilistic classifier based on applying Bayes' theorem with strong independence assumptions. A more descriptive term for the underlying probability model would …
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a graphical representation of the frequencies of a continuous variable. The variable is divided into bins and a bar is drawn for each bin, proportional to its frequency in the data.
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The Cox proportional hazards model (sometimes simply called the Cox model) refers to a method of survival analysis. Its great advantage is that it does not require specification of the hazard function…
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Ranking means identifying the ordering from highest to lowest or vice versa; statistical ranks are the values 1, 2, 3, ..., up to the sample size, assigned to values or attributes which have the highe…
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The quantiles of a distribution refer to points on its cumulative distribution function. Some common quantiles are quartiles and percentiles.
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Convergence generally means that a sequence of a certain sample quantity approaches a constant as the sample size tends to infinity.
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Distance functions refer to functions used for quantifying the notion of distance between members of a set, or between objects.
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Causal inference tries to quantify the effect of a change in $X$ on $Y$ whilst holding constant or eliminating all other relevant factors which might influence this relationship.
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a test for goodness of fit of data to a distribution. It is often used to test whether a variable is normally distributed.
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used for modelling systems that are assumed to be Markov processes with hidden (i.e. unobserved) states.
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The science of statistics applied to the analysis of biological or medical data.
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Refers to any statistical complication or problem due to having few data.
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In biostatistics, fixed-effects may mean population-average effects. In econometrics, fixed-effects may represent the observed quantities in terms of explanatory variables that are treated as if the q…
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one that is written as a convex combination of other distributions.
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called continuous if its set of possible values is uncountable, and the chance that it takes any particular value is zero ($\text{P}(X = x) = 0$ for every real number $x$). A …
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related to STATISTICS, MACHINE LEARNING, or DATA ANALYSIS and is not solely about programming, support, or bugs. Include additional tags referring to the statistical issues …
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The uniform distribution describes a random variable that is equally likely to take any value in its sample space.
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Generalized Linear Mixed (effects) Models are typically used for modeling non-independent non-normal data (eg, longitudinal binary data).
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Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS." (http://mcmc-jags.sourcefo…
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one whose joint distribution is constant over time. A weakly stationary process or series is one whose mean and covariance function (variance and autocorrelati…
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Skewness measures (or refers to) a degree of asymmetry in the distribution of a variable.
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Refers to the probability distribution of parameters conditioned on data in Bayesian statistics.
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Tables of counts (occasionally proportions of marginal counts), arranged by (at least) two marginal categories, displaying bivariate or multivariate frequencies. Sometimes called crosstabs.
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Descriptive statistics summarize features of a sample, such as mean and standard deviations, median and quartiles, the maximum and minimum. With multiple variables, may include correlations and crosst…
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A distribution describing the time between events in a Poisson process; a continuous analogue of the geometric distribution.
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Refers to an estimator of a population parameter that "hits the true value" on average. That is, a function of the observed data $\hat{\theta}$ is an unbiased estimator of a parameter $\theta$ if $E(\…
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the process of assessing whether the results of an analysis are likely to hold outside of the original research setting. DO NOT use this tag for discussing `validity` of a measurement or…