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  2. Rule of three (statistics) - Wikipedia

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

    Rule of three (statistics) In statistical analysis, the rule of three states that if a certain event did not occur in a sample with n subjects, the interval from 0 to 3/ n is a 95% confidence interval for the rate of occurrences in the population. When n is greater than 30, this is a good approximation of results from more sensitive tests.

  3. Optimal stopping - Wikipedia

    en.wikipedia.org/wiki/Optimal_stopping

    Optimal stopping. In mathematics, the theory of optimal stopping [1] [2] or early stopping [3] is concerned with the problem of choosing a time to take a particular action, in order to maximise an expected reward or minimise an expected cost. Optimal stopping problems can be found in areas of statistics, economics, and mathematical finance ...

  4. Trachtenberg system - Wikipedia

    en.wikipedia.org/wiki/Trachtenberg_system

    Trachtenberg system. The Trachtenberg system is a system of rapid mental calculation. The system consists of a number of readily memorized operations that allow one to perform arithmetic computations very quickly. It was developed by the Russian engineer Jakow Trachtenberg in order to keep his mind occupied while being in a Nazi concentration ...

  5. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3ss, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.

  6. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    Probability theory. In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is. The parameter is the mean or expectation of the distribution (and also its median and mode ), while ...

  7. Estimator - Wikipedia

    en.wikipedia.org/wiki/Estimator

    In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity of interest (the estimand) and its result (the estimate) are distinguished. [1] For example, the sample mean is a commonly used estimator of the population mean .

  8. Law of the unconscious statistician - Wikipedia

    en.wikipedia.org/wiki/Law_of_the_unconscious...

    In probability theory and statistics, the law of the unconscious statistician, or LOTUS, is a theorem which expresses the expected value of a function g(X) of a random variable X in terms of g and the probability distribution of X . The form of the law depends on the type of random variable X in question. If the distribution of X is discrete ...

  9. Independence (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Independence_(probability...

    Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes. Two events are independent, statistically independent, or stochastically independent [1] if, informally speaking, the occurrence of one does not affect the probability of occurrence of the other or, equivalently, does not affect ...