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  2. Event (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Event_(probability_theory)

    A single outcome may be an element of many different events, [2] and different events in an experiment are usually not equally likely, since they may include very different groups of outcomes. [3] An event consisting of only a single outcome is called an elementary event or an atomic event; that is, it is a singleton set.

  3. Elementary event - Wikipedia

    en.wikipedia.org/wiki/Elementary_event

    In probability theory, an elementary event, also called an atomic event or sample point, is an event which contains only a single outcome in the sample space. [1] Using set theory terminology, an elementary event is a singleton. Elementary events and their corresponding outcomes are often written interchangeably for simplicity, as such an event ...

  4. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    In the absolutely continuous case, probabilities are described by a probability density function, and the probability distribution is by definition the integral of the probability density function. [7] [4] [8] The normal distribution is a commonly encountered absolutely continuous probability distribution.

  5. Singular perturbation - Wikipedia

    en.wikipedia.org/wiki/Singular_perturbation

    A perturbed problem whose solution can be approximated on the whole problem domain, whether space or time, by a single asymptotic expansion has a regular perturbation.Most often in applications, an acceptable approximation to a regularly perturbed problem is found by simply replacing the small parameter by zero everywhere in the problem statement.

  6. Probability space - Wikipedia

    en.wikipedia.org/wiki/Probability_space

    Here, an "event" is a set of zero or more outcomes; that is, a subset of the sample space. An event is considered to have "happened" during an experiment when the outcome of the latter is an element of the event. Since the same outcome may be a member of many events, it is possible for many events to have happened given a single outcome.

  7. Marginal distribution - Wikipedia

    en.wikipedia.org/wiki/Marginal_distribution

    The marginal probability is the probability of a single event occurring, independent of other events. A conditional probability, on the other hand, is the probability that an event occurs given that another specific event has already occurred. This means that the calculation for one variable is dependent on another variable. [2]

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