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  2. Probabilistic method - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_method

    Alternatively, the probabilistic method can also be used to guarantee the existence of a desired element in a sample space with a value that is greater than or equal to the calculated expected value, since the non-existence of such element would imply every element in the sample space is less than the expected value, a contradiction.

  3. Lottery mathematics - Wikipedia

    en.wikipedia.org/wiki/Lottery_mathematics

    An alternative method of calculating the odds is to note that the probability of the first ball corresponding to one of the six chosen is 6/49; the probability of the second ball corresponding to one of the remaining five chosen is 5/48; and so on. This yields a final formula of

  4. Probability - Wikipedia

    en.wikipedia.org/wiki/Probability

    Governments apply probabilistic methods in environmental regulation, entitlement analysis, and financial regulation. An example of the use of probability theory in equity trading is the effect of the perceived probability of any widespread Middle East conflict on oil prices, which have ripple effects in the economy as a whole.

  5. Bootstrapping (statistics) - Wikipedia

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

    This method uses Gaussian process regression (GPR) to fit a probabilistic model from which replicates may then be drawn. GPR is a Bayesian non-linear regression method. A Gaussian process (GP) is a collection of random variables, any finite number of which have a joint Gaussian (normal) distribution.

  6. Method of conditional probabilities - Wikipedia

    en.wikipedia.org/wiki/Method_of_conditional...

    The method is particularly relevant in the context of randomized rounding (which uses the probabilistic method to design approximation algorithms). When applying the method of conditional probabilities, the technical term pessimistic estimator refers to a quantity used in place of the true conditional probability (or conditional expectation ...

  7. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    Let be a discrete random variable with probability mass function depending on a parameter .Then the function = = (=),considered as a function of , is the likelihood function, given the outcome of the random variable .

  8. Maximum likelihood estimation - Wikipedia

    en.wikipedia.org/wiki/Maximum_likelihood_estimation

    In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data.This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable.

  9. Fisher's method - Wikipedia

    en.wikipedia.org/wiki/Fisher's_method

    Under Fisher's method, two small p-values P 1 and P 2 combine to form a smaller p-value.The darkest boundary defines the region where the meta-analysis p-value is below 0.05.. For example, if both p-values are around 0.10, or if one is around 0.04 and one is around 0.25, the meta-analysis p-value is around 0