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  2. 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]

  3. Probability - Wikipedia

    en.wikipedia.org/wiki/Probability

    Conditional probability is the probability of some event A, given the occurrence of some other event B. Conditional probability is written (), and is read "the probability of A, given B". It is defined by [33] = ()

  4. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The triangular distribution on [a, b], a special case of which is the distribution of the sum of two independent uniformly distributed random variables (the convolution of two uniform distributions). The trapezoidal distribution; The truncated normal distribution on [a, b]. The U-quadratic distribution on [a, b].

  5. Conditional probability distribution - Wikipedia

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

    Then the unconditional probability that = is 3/6 = 1/2 (since there are six possible rolls of the dice, of which three are even), whereas the probability that = conditional on = is 1/3 (since there are three possible prime number rolls—2, 3, and 5—of which one is even).

  6. Chain rule (probability) - Wikipedia

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

    This rule allows one to express a joint probability in terms of only conditional probabilities. [4] The rule is notably used in the context of discrete stochastic processes and in applications, e.g. the study of Bayesian networks, which describe a probability distribution in terms of conditional probabilities.

  7. Conditional probability table - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability_table

    The first column sum is the probability that x =0 and y equals any of the values it can have – that is, the column sum 6/9 is the marginal probability that x=0. If we want to find the probability that y=0 given that x=0, we compute the fraction of the probabilities in the x=0 column that have the value y=0, which is 4/9 ÷

  8. (a,b,0) class of distributions - Wikipedia

    en.wikipedia.org/wiki/(a,b,0)_class_of_distributions

    However, some further well-known distributions are available if the recursion above need only hold for a restricted range of values of k: [5] for example the logarithmic distribution and the discrete uniform distribution. The (a, b, 0) class of distributions has important applications in actuarial science in the context of loss models. [6]

  9. Law of total probability - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_probability

    The term law of total probability is sometimes taken to mean the law of alternatives, which is a special case of the law of total probability applying to discrete random variables. [ citation needed ] One author uses the terminology of the "Rule of Average Conditional Probabilities", [ 4 ] while another refers to it as the "continuous law of ...

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