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  2. Conditional probability - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability

    However, the conditional probability P(A|B 1) = 1, P(A|B 2) = 0.12 ÷ (0.12 + 0.04) = 0.75, and P(A|B 3) = 0. On a tree diagram, branch probabilities are conditional on the event associated with the parent node. (Here, the overbars indicate that the event does not occur.) Venn Pie Chart describing conditional probabilities

  3. Bayes' theorem - Wikipedia

    en.wikipedia.org/wiki/Bayes'_theorem

    P(A) is the proportion of outcomes with property A (the prior) and P(B) is the proportion with property B. P(B | A) is the proportion of outcomes with property B out of outcomes with property A, and P(A | B) is the proportion of those with A out of those with B (the posterior). The role of Bayes' theorem can be shown with tree diagrams.

  4. Conditional independence - Wikipedia

    en.wikipedia.org/wiki/Conditional_independence

    In probability theory, conditional independence describes situations wherein an observation is irrelevant or redundant when evaluating the certainty of a hypothesis. . Conditional independence is usually formulated in terms of conditional probability, as a special case where the probability of the hypothesis given the uninformative observation is equal to the probability

  5. Law of total probability - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_probability

    [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 alternatives" in the continuous case. [5] This result is given by Grimmett and Welsh [6] as the partition theorem, a name that they also give to the related law of total expectation.

  6. Probability axioms - Wikipedia

    en.wikipedia.org/wiki/Probability_axioms

    Setting B to the complement A c of A in the addition law gives P ( A c ) = P ( Ω ∖ A ) = 1 − P ( A ) {\displaystyle P\left(A^{c}\right)=P(\Omega \setminus A)=1-P(A)} That is, the probability that any event will not happen (or the event's complement ) is 1 minus the probability that it will.

  7. Independence (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Independence_(probability...

    Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes.Two events are independent, statistically independent, or stochastically independent [1] if, informally speaking, the occurrence of one does not affect the probability of occurrence of the other or, equivalently, does not affect the odds.

  8. Quadratic formula - Wikipedia

    en.wikipedia.org/wiki/Quadratic_formula

    A similar but more complicated method works for cubic equations, which have three resolvents and a quadratic equation (the "resolving polynomial") relating ⁠ ⁠ and ⁠ ⁠, which one can solve by the quadratic equation, and similarly for a quartic equation (degree 4), whose resolving polynomial is a cubic, which can in turn be solved. [14]

  9. Pythagorean triple - Wikipedia

    en.wikipedia.org/wiki/Pythagorean_triple

    If c = p e is a prime power, there exists a primitive Pythagorean triple a 2 + b 2 = c 2 if and only if the prime p has the form 4n + 1; this triple is unique up to the exchange of a and b. More generally, a positive integer c is the hypotenuse of a primitive Pythagorean triple if and only if each prime factor of c is congruent to 1 modulo 4 ...