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  2. All models are wrong - Wikipedia

    en.wikipedia.org/wiki/All_models_are_wrong

    George Box. The phrase "all models are wrong" was first attributed to George Box in a 1976 paper published in the Journal of the American Statistical Association.In the paper, Box uses the phrase to refer to the limitations of models, arguing that while no model is ever completely accurate, simpler models can still provide valuable insights if applied judiciously. [2]

  3. Criticisms of econometrics - Wikipedia

    en.wikipedia.org/wiki/Criticisms_of_econometrics

    Lucas argued a good macroeconometric model should incorporate microfoundations to model the effects of policy change, with equations representing economic representative agents responding to economic changes based on rational expectations of the future; implying their pattern of behaviour might be quite different if economic policy changed.

  4. Statistical model specification - Wikipedia

    en.wikipedia.org/wiki/Statistical_model...

    The purpose of the comparison is to determine which candidate model is most appropriate for statistical inference. Common criteria for comparing models include the following: R 2, Bayes factor, and the likelihood-ratio test together with its generalization relative likelihood. For more on this topic, see statistical model selection.

  5. Tukey's range test - Wikipedia

    en.wikipedia.org/wiki/Tukey's_range_test

    Since the null hypothesis for Tukey's test states that all means being compared are from the same population (i.e. μ 1 = μ 2 = μ 3 = ... = μ k), the means should be normally distributed (according to the central limit theorem) with the same model standard deviation σ, estimated by the merged standard error, , for all the samples; its ...

  6. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    Statistical hypothesis testing is a key technique of both frequentist inference and Bayesian inference, although the two types of inference have notable differences. Statistical hypothesis tests define a procedure that controls (fixes) the probability of incorrectly deciding that a default position (null hypothesis) is incorrect. The procedure ...

  7. Foundations of statistics - Wikipedia

    en.wikipedia.org/wiki/Foundations_of_statistics

    Statistics subsequently branched out into various directions, including decision theory, Bayesian statistics, exploratory data analysis, robust statistics, and non-parametric statistics. Neyman-Pearson hypothesis testing made significant contributions to decision theory, which is widely employed, particularly in statistical quality control.

  8. Relative index of inequality - Wikipedia

    en.wikipedia.org/wiki/Relative_index_of_inequality

    The relative index of inequality (RII) is a regression-based index which summarizes the magnitude of socio-economic status (SES) as a source of inequalities in health. RII is useful because it takes into account the size of the population and the relative disadvantage experienced by different groups. [1]

  9. Asymptotic theory (statistics) - Wikipedia

    en.wikipedia.org/wiki/Asymptotic_theory_(statistics)

    In statistics, asymptotic theory, or large sample theory, is a framework for assessing properties of estimators and statistical tests. Within this framework, it is often assumed that the sample size n may grow indefinitely; the properties of estimators and tests are then evaluated under the limit of n → ∞. In practice, a limit evaluation is ...