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  2. Urn problem - Wikipedia

    en.wikipedia.org/wiki/Urn_problem

    Two urns containing white and red balls. In probability and statistics, an urn problem is an idealized mental exercise in which some objects of real interest (such as atoms, people, cars, etc.) are represented as colored balls in an urn or other container. One pretends to remove one or more balls from the urn; the goal is to determine the ...

  3. Multiple comparisons problem - Wikipedia

    en.wikipedia.org/wiki/Multiple_comparisons_problem

    However, if one considers 100 confidence intervals simultaneously, each with 95% coverage probability, the expected number of non-covering intervals is 5. If the intervals are statistically independent from each other, the probability that at least one interval does not contain the population parameter is 99.4%.

  4. Sample space - Wikipedia

    en.wikipedia.org/wiki/Sample_space

    A well-defined, non-empty sample space is one of three components in a probabilistic model (a probability space). The other two basic elements are a well-defined set of possible events (an event space), which is typically the power set of if is discrete or a σ-algebra on if it is continuous, and a probability assigned to each event (a ...

  5. Rule of succession - Wikipedia

    en.wikipedia.org/wiki/Rule_of_succession

    In probability theory, the rule of succession is a formula introduced in the 18th century by Pierre-Simon Laplace in the course of treating the sunrise problem. [1] The formula is still used, particularly to estimate underlying probabilities when there are few observations or events that have not been observed to occur at all in (finite) sample data.

  6. Hypergeometric distribution - Wikipedia

    en.wikipedia.org/wiki/Hypergeometric_distribution

    In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the probability of successes (random draws for which the object drawn has a specified feature) in draws, without replacement, from a finite population of size that contains exactly objects with that feature, wherein each draw is either a success or a failure.

  7. Axiom of choice - Wikipedia

    en.wikipedia.org/wiki/Axiom_of_choice

    Then the set X = {{x 1, y 1}, {x 2, y 2}, {x 3, y 3}, ...} can be in the model but sets such as {x 1, x 2, x 3, ...} cannot, and thus X cannot have a choice function. In 1938, [ 19 ] Kurt Gödel showed that the negation of the axiom of choice is not a theorem of ZF by constructing an inner model (the constructible universe ) that satisfies ZFC ...

  8. Mutual exclusivity - Wikipedia

    en.wikipedia.org/wiki/Mutual_exclusivity

    The probability of drawing a red and a club in two drawings without replacement is then 26/52 × 13/51 × 2 = 676/2652, or 13/51. With replacement, the probability would be 26/52 × 13/52 × 2 = 676/2704, or 13/52. In probability theory, the word or allows for the possibility of both events happening

  9. Probability space - Wikipedia

    en.wikipedia.org/wiki/Probability_space

    These two non-atomic examples are closely related: a sequence (x 1, x 2, ...) ∈ {0,1} ∞ leads to the number 2 −1 x 1 + 22 x 2 + ⋯ ∈ [0,1]. This is not a one-to-one correspondence between {0,1} ∞ and [0,1] however: it is an isomorphism modulo zero, which allows for treating the two probability spaces as two forms of the same ...