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  2. Law of triviality - Wikipedia

    en.wikipedia.org/wiki/Law_of_triviality

    The law of triviality is C. Northcote Parkinson's 1957 argument that people within an organization commonly give disproportionate weight to trivial issues. [1] Parkinson provides the example of a fictional committee whose job was to approve the plans for a nuclear power plant spending the majority of its time on discussions about relatively minor but easy-to-grasp issues, such as what ...

  3. Three cups problem - Wikipedia

    en.wikipedia.org/wiki/Three_cups_problem

    The solvable version of the problem. Here, cups A and C are upside down, and cup B is upright. The three cups problem, also known as the three cup challenge and other variants, is a mathematical puzzle that, in its most common form, cannot be solved. In the beginning position of the problem, one cup is upside-down and the other two are right ...

  4. Proportionality (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Proportionality_(mathematics)

    Hence the constant "k" is the product of x and y. The graph of two variables varying inversely on the Cartesian coordinate plane is a rectangular hyperbola. The product of the x and y values of each point on the curve equals the constant of proportionality (k). Since neither x nor y can equal zero (because k is non-zero), the graph never ...

  5. Inverse probability weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse_probability_weighting

    Inverse probability weighting is a statistical technique for estimating quantities related to a population other than the one from which the data was collected. Study designs with a disparate sampling population and population of target inference (target population) are common in application. [ 1 ]

  6. Inverse-variance weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse-variance_weighting

    For normally distributed random variables inverse-variance weighted averages can also be derived as the maximum likelihood estimate for the true value. Furthermore, from a Bayesian perspective the posterior distribution for the true value given normally distributed observations and a flat prior is a normal distribution with the inverse-variance weighted average as a mean and variance ().

  7. Inverse distribution - Wikipedia

    en.wikipedia.org/wiki/Inverse_distribution

    Inverse distributions arise in particular in the Bayesian context of prior distributions and posterior distributions for scale parameters. In the algebra of random variables , inverse distributions are special cases of the class of ratio distributions , in which the numerator random variable has a degenerate distribution .