statistic model

  • 1Model 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 …

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  • 2Statistic (role-playing games) — Part of a series on …

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  • 3Statistical model validation — Model validation is possibly the most important step in the model building sequence. It is also one of the most overlooked. Often the validation of a model seems to consist of nothing more than quoting the R 2 statistic from the fit (which… …

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  • 4Durbin–Watson statistic — In statistics, the Durbin–Watson statistic is a test statistic used to detect the presence of autocorrelation (a relationship between values separated from each other by a given time lag) in the residuals (prediction errors) from a regression… …

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  • 5Sufficient 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… …

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  • 6Rasch model — Rasch models are used for analysing data from assessments to measure things such as abilities, attitudes, and personality traits. For example, they may be used to estimate a student s reading ability from answers to questions on a reading… …

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  • 7Summary statistic — Box plot of the Michelson–Morley experiment, showing several summary statistics. In descriptive statistics, summary statistics are used to summarize a set of observations, in order to communicate the largest amount as simply as possible.… …

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  • 8PRESS statistic — In statistics, the predicted residual sums of squares (PRESS) statistic is used in regression analysis to provide a summary measure of the fit of a model to a sample of observations. These observation were not themselves used to estimate the… …

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  • 9Regression model validation — In statistics, model validation is possibly the most important step in the model building sequence. It is also one of the most overlooked.[citation needed] Often the validation of a model seems to consist of nothing more than quoting the R2… …

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  • 10Generalized linear model — In statistics, the generalized linear model (GLM) is a flexible generalization of ordinary least squares regression. It relates the random distribution of the measured variable of the experiment (the distribution function ) to the systematic (non …

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