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  2. Mutual exclusivity - Wikipedia

    en.wikipedia.org/wiki/Mutual_exclusivity

    In logic, two propositions and are mutually exclusive if it is not logically possible for them to be true at the same time; that is, () is a tautology. To say that more than two propositions are mutually exclusive, depending on the context, means either 1. "() () is a tautology" (it is not logically possible for more than one proposition to be true) or 2. "() is a tautology" (it is not ...

  3. Craps principle - Wikipedia

    en.wikipedia.org/wiki/Craps_principle

    In probability theory, the craps principle is a theorem about event probabilities under repeated iid trials. Let and denote two mutually exclusive events which might occur on a given trial.

  4. Collectively exhaustive events - Wikipedia

    en.wikipedia.org/wiki/Collectively_exhaustive_events

    Another example of events being collectively exhaustive and mutually exclusive at same time are, event "even" (2,4 or 6) and event "odd" (1,3 or 5) in a random experiment of rolling a six-sided die. These both events are mutually exclusive because even and odd outcome can never occur at same time. The union of both "even" and "odd" events give ...

  5. 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.

  6. Complementary event - Wikipedia

    en.wikipedia.org/wiki/Complementary_event

    The event A and its complement [not A] are mutually exclusive and exhaustive. Generally, there is only one event B such that A and B are both mutually exclusive and exhaustive; that event is the complement of A. The complement of an event A is usually denoted as A′, A c, A or A.

  7. Law of total probability - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_probability

    The law of total probability is [1] a theorem that states, in its discrete case, if {: =,,, …} is a finite or countably infinite set of mutually exclusive and collectively exhaustive events, then for any event () = ()

  8. Probability space - Wikipedia

    en.wikipedia.org/wiki/Probability_space

    Two events, A and B are said to be mutually exclusive or disjoint if the occurrence of one implies the non-occurrence of the other, i.e., their intersection is empty. This is a stronger condition than the probability of their intersection being zero.

  9. Experiment (probability theory) - Wikipedia

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

    A random experiment that has exactly two (mutually exclusive) possible outcomes is known as a Bernoulli trial. [ 2 ] When an experiment is conducted, one (and only one) outcome results— although this outcome may be included in any number of events , all of which would be said to have occurred on that trial.