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  2. Poisson distribution - Wikipedia

    en.wikipedia.org/wiki/Poisson_distribution

    For sufficiently large values of λ, (say λ >1000), the normal distribution with mean λ and variance λ (standard deviation ) is an excellent approximation to the Poisson distribution. If λ is greater than about 10, then the normal distribution is a good approximation if an appropriate continuity correction is performed, i.e., if P( X ≤ x ...

  3. Shot noise - Wikipedia

    en.wikipedia.org/wiki/Shot_noise

    Shot noise or Poisson noise is a type of noise which can be modeled by a Poisson process. In electronics shot noise originates from the discrete nature of electric charge . Shot noise also occurs in photon counting in optical devices, where shot noise is associated with the particle nature of light.

  4. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    Normal distribution; ... measure of the dispersion of the distribution. Standard deviation: ... the rate parameter of a Poisson distribution or exponential ...

  5. Photon statistics - Wikipedia

    en.wikipedia.org/wiki/Photon_statistics

    This last expression represents the intensity distribution for thermal light. The last step in showing thermal light satisfies the variance condition for super-Poisson statistics is to use Mandel's formula. [3] The formula describes the probability of observing n photon counts and is given by

  6. 68–95–99.7 rule - Wikipedia

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

    Diagram showing the cumulative distribution function for the normal distribution with mean (μ) 0 and variance (σ 2) 1. These numerical values "68%, 95%, 99.7%" come from the cumulative distribution function of the normal distribution. The prediction interval for any standard score z corresponds numerically to (1 − (1 − Φ μ,σ 2 (z)) · 2).

  7. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    The studentized bootstrap, also called bootstrap-t, is computed analogously to the standard confidence interval, but replaces the quantiles from the normal or student approximation by the quantiles from the bootstrap distribution of the Student's t-test (see Davison and Hinkley 1997, equ. 5.7 p. 194 and Efron and Tibshirani 1993 equ 12.22, p. 160):

  8. Negative binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Negative_binomial_distribution

    Different texts (and even different parts of this article) adopt slightly different definitions for the negative binomial distribution. They can be distinguished by whether the support starts at k = 0 or at k = r, whether p denotes the probability of a success or of a failure, and whether r represents success or failure, [1] so identifying the specific parametrization used is crucial in any ...

  9. Exponential distribution - Wikipedia

    en.wikipedia.org/wiki/Exponential_distribution

    In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate; the distance parameter could be any meaningful mono-dimensional measure of the process, such as time ...