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  2. List of important publications in statistics - Wikipedia

    en.wikipedia.org/wiki/List_of_important...

    Many examples and problems come from business and economics. Importance: Greatly extended the scope of applied Bayesian statistics by using conjugate priors for exponential families. Extensive treatment of sequential decision making, for example mining decisions. For many years, it was required for all doctoral students at Harvard Business School.

  3. Foundations of statistics - Wikipedia

    en.wikipedia.org/wiki/Foundations_of_statistics

    Frequentist interpret the likelihood principle unfavourably, as it suggests a lack of concern for the reliability of evidence. The likelihood principle, according to Bayesian statistics, implies that information about the experimental design used to collect evidence does not factor into the statistical analysis of the data. [39]

  4. Statistical theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_theory

    The theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. [1] [2] The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches.

  5. Category:Statistical principles - Wikipedia

    en.wikipedia.org/.../Category:Statistical_principles

    Pages in category "Statistical principles" The following 14 pages are in this category, out of 14 total. ... Statistics; Cookie statement; Mobile view ...

  6. Glivenko–Cantelli theorem - Wikipedia

    en.wikipedia.org/wiki/Glivenko–Cantelli_theorem

    In the theory of probability, the Glivenko–Cantelli theorem (sometimes referred to as the Fundamental Theorem of Statistics), named after Valery Ivanovich Glivenko and Francesco Paolo Cantelli, describes the asymptotic behaviour of the empirical distribution function as the number of independent and identically distributed observations grows. [1]

  7. Statistical model - Wikipedia

    en.wikipedia.org/wiki/Statistical_model

    In this example, the dimension, k, equals 2. As another example, suppose that the data consists of points (x, y) that we assume are distributed according to a straight line with i.i.d. Gaussian residuals (with zero mean): this leads to the same statistical model as was used in the example with children's heights. The dimension of the ...

  8. Neyman–Pearson lemma - Wikipedia

    en.wikipedia.org/wiki/Neyman–Pearson_lemma

    Neyman–Pearson lemma [5] — Existence:. If a hypothesis test satisfies condition, then it is a uniformly most powerful (UMP) test in the set of level tests.. Uniqueness: If there exists a hypothesis test that satisfies condition, with >, then every UMP test in the set of level tests satisfies condition with the same .

  9. Empirical statistical laws - Wikipedia

    en.wikipedia.org/wiki/Empirical_statistical_laws

    The Pareto principle is a popular example of such a "law". It states that roughly 80% of the effects come from 20% of the causes, and is thus also known as the 80/20 rule. [ 2 ] In business, the 80/20 rule says that 80% of your business comes from just 20% of your customers. [ 3 ]