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  2. 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.

  3. 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 ...

  4. Probability - Wikipedia

    en.wikipedia.org/wiki/Probability

    If either event A or event B can occur but never both simultaneously, then they are called mutually exclusive events. If two events are mutually exclusive, then the probability of both occurring is denoted as () and = = If two events are mutually exclusive, then the probability of either occurring is denoted as () and = = + () = + = + ()

  5. 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 ...

  6. Probability theory - Wikipedia

    en.wikipedia.org/wiki/Probability_theory

    This is the same as saying that the probability of event {1,2,3,4,6} is 5/6. This event encompasses the possibility of any number except five being rolled. The mutually exclusive event {5} has a probability of 1/6, and the event {1,2,3,4,5,6} has a probability of 1, that is, absolute certainty.

  7. Independent and identically distributed random variables

    en.wikipedia.org/wiki/Independent_and...

    Independent: Each outcome of the die roll will not affect the next one, which means the 10 variables are independent from each other. Identically distributed : Regardless of whether the die is fair or weighted, each roll will have the same probability of seeing each result as every other roll.

  8. 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 ...

  9. Pairwise independence - Wikipedia

    en.wikipedia.org/wiki/Pairwise_independence

    In probability theory, a pairwise independent collection of random variables is a set of random variables any two of which are independent. [1] Any collection of mutually independent random variables is pairwise independent, but some pairwise independent collections are not mutually independent.