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  2. Bertrand's ballot theorem - Wikipedia

    en.wikipedia.org/wiki/Bertrand's_ballot_theorem

    Then considering the case with p = a and q = b, the last vote counted is either for the first candidate with probability a/(a + b), or for the second with probability b/(a + b). So the probability of the first being ahead throughout the count to the penultimate vote counted (and also after the final vote) is:

  3. Conditional probability - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability

    Given two events A and B from the sigma-field of a probability space, with the unconditional probability of B being greater than zero (i.e., P(B) > 0), the conditional probability of A given B (()) is the probability of A occurring if B has or is assumed to have happened. [5]

  4. Conditional probability distribution - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability...

    Seen as a function of for given , (= | =) is a probability mass function and so the sum over all (or integral if it is a conditional probability density) is 1. Seen as a function of x {\displaystyle x} for given y {\displaystyle y} , it is a likelihood function , so that the sum (or integral) over all x {\displaystyle x} need not be 1.

  5. Characteristic function (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Characteristic_function...

    If, on the other hand, we know the characteristic function φ and want to find the corresponding distribution function, then one of the following inversion theorems can be used. Theorem. If the characteristic function φ X of a random variable X is integrable, then F X is absolutely continuous, and therefore X has a probability density function.

  6. Probability - Wikipedia

    en.wikipedia.org/wiki/Probability

    Probability is the branch of mathematics and statistics concerning events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the larger the probability, the more likely an event is to occur. [note 1] [1] [2] This number is often expressed as a percentage (%), ranging from 0% to ...

  7. De Morgan's laws - Wikipedia

    en.wikipedia.org/wiki/De_Morgan's_laws

    De Morgan's laws represented with Venn diagrams.In each case, the resultant set is the set of all points in any shade of blue. In propositional logic and Boolean algebra, De Morgan's laws, [1] [2] [3] also known as De Morgan's theorem, [4] are a pair of transformation rules that are both valid rules of inference.

  8. Probability bounds analysis - Wikipedia

    en.wikipedia.org/wiki/Probability_bounds_analysis

    Thus the probability that A is less than B is the same as the probability that their difference is less than zero, and this probability can be said to be the value of the expression A < B. Like arithmetic and logical operations, these magnitude comparisons generally depend on the stochastic dependence between A and B , and the subtraction in ...

  9. Buffon's needle problem - Wikipedia

    en.wikipedia.org/wiki/Buffon's_needle_problem

    For simplicity in the algebraic formulation ahead, let a = b = t = 2l such that the original result in Buffon's problem is P(A) = P(B) = ⁠ 1 / π ⁠. Furthermore, let N = 100 drops. Now let us examine P(AB) for Laplace's result, that is, the probability the needle intersects both a horizontal and a vertical line. We know that