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  2. Empirical probability - Wikipedia

    en.wikipedia.org/wiki/Empirical_probability

    In probability theory and statistics, the empirical probability, relative frequency, or experimental probability of an event is the ratio of the number of outcomes in which a specified event occurs to the total number of trials, [1] i.e. by means not of a theoretical sample space but of an actual experiment.

  3. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of possible outcomes for an experiment. [ 1 ] [ 2 ] It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events ( subsets of the sample space).

  4. Bernoulli trial - Wikipedia

    en.wikipedia.org/wiki/Bernoulli_trial

    Graphs of probability P of not observing independent events each of probability p after n Bernoulli trials vs np for various p.Three examples are shown: Blue curve: Throwing a 6-sided die 6 times gives a 33.5% chance that 6 (or any other given number) never turns up; it can be observed that as n increases, the probability of a 1/n-chance event never appearing after n tries rapidly converges to ...

  5. Sample space - Wikipedia

    en.wikipedia.org/wiki/Sample_space

    In this case, the above formula applies, such as calculating the probability of a particular sum of the two rolls in an outcome. The probability of the event that the sum D 1 + D 2 {\displaystyle D_{1}+D_{2}} is five is 4 36 {\displaystyle {\frac {4}{36}}} , since four of the thirty-six equally likely pairs of outcomes sum to five.

  6. Chain rule (probability) - Wikipedia

    en.wikipedia.org/wiki/Chain_rule_(probability)

    In probability theory, the chain rule [1] (also called the general product rule [2] [3]) describes how to calculate the probability of the intersection of, not necessarily independent, events or the joint distribution of random variables respectively, using conditional probabilities.

  7. Approximate Bayesian computation - Wikipedia

    en.wikipedia.org/wiki/Approximate_Bayesian...

    A strictly positive tolerance is usually necessary, since the probability that the simulation outcome coincides exactly with the data (event ^ =) is negligible for all but trivial applications of ABC, which would in practice lead to rejection of nearly all sampled parameter points. The outcome of the ABC rejection algorithm is a sample of ...

  8. Probability - Wikipedia

    en.wikipedia.org/wiki/Probability

    The probabilities of rolling several numbers using two dice. 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.

  9. CHSH inequality - Wikipedia

    en.wikipedia.org/wiki/CHSH_inequality

    In experimental practice, the two particles are not an ideal EPR pair. There is a necessary and sufficient condition for a two- qubit density matrix ρ {\displaystyle \rho } to violate the CHSH inequality, expressed by the maximum attainable polynomial S max defined in Eq. 2 . [ 13 ]