bayesian criterion
31Sufficient statistic — In statistics, a sufficient statistic is a statistic which has the property of sufficiency with respect to a statistical model and its associated unknown parameter, meaning that no other statistic which can be calculated from the same sample… …
32Model selection — is the task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre existing set of data is considered. However, the task can also involve the design of experiments such that the data collected is …
33Computerized classification test — A computerized classification test (CCT) refers to, as its name would suggest, a test that is administered by computer for the purpose of classifying examinees. The most common CCT is a mastery test where the test classifies examinees as Pass or… …
34Statistical hypothesis testing — This article is about frequentist hypothesis testing which is taught in introductory statistics. For Bayesian hypothesis testing, see Bayesian inference. A statistical hypothesis test is a method of making decisions using data, whether from a… …
35Kullback–Leibler divergence — In probability theory and information theory, the Kullback–Leibler divergence[1][2][3] (also information divergence, information gain, relative entropy, or KLIC) is a non symmetric measure of the difference between two probability distributions P …
36Info-gap decision theory — is a non probabilistic decision theory that seeks to optimize robustness to failure – or opportuneness for windfall – under severe uncertainty,[1][2] in particular applying sensitivity analysis of the stability radius type[3] to perturbations in… …
37Least squares — The method of least squares is a standard approach to the approximate solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of… …
38Deviance (statistics) — In statistics, deviance is a quality of fit statistic for a model that is often used for statistical hypothesis testing. The deviance for a model M0 is defined as Here denotes the fitted values of the parameters in the model M0, while denotes the …
39Distance matrices in phylogeny — Distance matrices are used in phylogeny as non parametric distance methods were originally applied to phenetic data using a matrix of pairwise distances. These distances are then reconciled to produce a tree (a phylogram, with informative branch… …
40Multiple comparisons — In statistics, the multiple comparisons or multiple testing problem occurs when one considers a set of statistical inferences simultaneously.[1] Errors in inference, including confidence intervals that fail to include their corresponding… …
