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  2. Empirical probability - Wikipedia

    en.wikipedia.org/wiki/Empirical_probability

    In probability theory and statistics, the empirical probability, relative frequency, or experimental probability of an event is the ratio of the number of outcomes in which a specified event occurs to the total number of trials, [1] i.e. by means not of a theoretical sample space but of an actual experiment.

  3. Experiment (probability theory) - Wikipedia

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

    In probability theory, an experiment or trial (see below) is any procedure that can be infinitely repeated and has a well-defined set of possible outcomes, known as the sample space. [1] An experiment is said to be random if it has more than one possible outcome, and deterministic if it has only one.

  4. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In the empirical sciences, the so-called three-sigma rule of thumb (or 3 σ rule) expresses a conventional heuristic that nearly all values are taken to lie within three standard deviations of the mean, and thus it is empirically useful to treat 99.7% probability as near certainty.

  5. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of possible outcomes for an experiment. [1] [2] It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). [3]

  6. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    Small samples are somewhat more likely to underestimate the population standard deviation and have a mean that differs from the true population mean, and the Student t-distribution accounts for the probability of these events with somewhat heavier tails compared to a Gaussian.

  7. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    Let 1 A denote the indicator function of an event A, then E[1 A] is given by the probability of A. This is nothing but a different way of stating the expectation of a Bernoulli random variable , as calculated in the table above.

  8. Statistical model - Wikipedia

    en.wikipedia.org/wiki/Statistical_model

    The alternative statistical assumption is this: for each of the dice, the probability of the face 5 coming up is ⁠ 1 / 8 ⁠ (because the dice are weighted). From that assumption, we can calculate the probability of both dice coming up 5: ⁠ 1 / 8 ⁠ × ⁠ 1 / 8 ⁠ = ⁠ 1 / 64 ⁠.

  9. Probability - Wikipedia

    en.wikipedia.org/wiki/Probability

    Probability is the branch of mathematics and statistics concerning events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the larger the probability, the more likely an event is to occur. [note 1] [1] [2] This number is often expressed as a percentage (%), ranging from 0% to ...