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  2. Mathematical statistics - Wikipedia

    en.wikipedia.org/wiki/Mathematical_statistics

    Mathematical statistics is the application of probability theory and other mathematical concepts to statistics, as opposed to techniques for collecting statistical data. [1] Specific mathematical techniques that are commonly used in statistics include mathematical analysis , linear algebra , stochastic analysis , differential equations , and ...

  3. Laplace's approximation - Wikipedia

    en.wikipedia.org/wiki/Laplace's_approximation

    "The Classical Laplace Method". Computational Bayesian Statistics : An Introduction. Cambridge: Cambridge University Press. pp. 154– 159. ISBN 978-1-108-48103-8. Tanner, Martin A. (1996). "Posterior Moments and Marginalization Based on Laplace's Method". Tools for Statistical Inference. New York: Springer. pp. 44– 51. ISBN 0-387-94688-8

  4. List of unsolved problems in statistics - Wikipedia

    en.wikipedia.org/wiki/List_of_unsolved_problems...

    Meta-analysis: Though independent p-values can be combined using Fisher's method, techniques are still being developed to handle the case of dependent p-values. Behrens–Fisher problem: Yuri Linnik showed in 1966 that there is no uniformly most powerful test for the difference of two means when the variances are unknown and possibly unequal.

  5. Foundations of statistics - Wikipedia

    en.wikipedia.org/wiki/Foundations_of_statistics

    No wonder that mathematicians find it often difficult to believe that conventional statistical methods are a branch of mathematics." [31] "Bayesianism is a neat and fully principled philosophy, while frequentist is a grab-bag of opportunistic, individually optimal, methods." [24] "In multiparameter problems flat priors can yield very bad ...

  6. Likelihood principle - Wikipedia

    en.wikipedia.org/wiki/Likelihood_principle

    Unrealized events play a role in some common statistical methods. For example, the result of a significance test depends on the p-value, the probability of a result as extreme or more extreme than the observation, and that probability may depend on the design of the experiment. To the extent that the likelihood principle is accepted, such ...

  7. Response surface methodology - Wikipedia

    en.wikipedia.org/wiki/Response_surface_methodology

    Response surface methodology uses statistical models, and therefore practitioners need to be aware that even the best statistical model is an approximation to reality. In practice, both the models and the parameter values are unknown, and subject to uncertainty on top of ignorance.

  8. Statistical Methods for Research Workers - Wikipedia

    en.wikipedia.org/wiki/Statistical_Methods_for...

    Statistical Methods for Research Workers is a classic book on statistics, written by the statistician R. A. Fisher. It is considered by some [ who? ] to be one of the 20th century's most influential books on statistical methods , together with his The Design of Experiments (1935).

  9. List of mathematics-based methods - Wikipedia

    en.wikipedia.org/wiki/List_of_mathematics-based...

    D'Hondt method (voting systems) D21 – Janeček method (voting system) Discrete element method (numerical analysis) Domain decomposition method (numerical analysis) Epidemiological methods; Euler's forward method; Explicit and implicit methods (numerical analysis) Finite difference method (numerical analysis) Finite element method (numerical ...