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  2. Barnard's test - Wikipedia

    en.wikipedia.org/wiki/Barnard's_test

    The probability of a 2 × 2 table under the first study design is given by the multinomial distribution; where the total number of samples taken is the only statistical constraint. This is a form of uncontrolled experiment, or "field observation", where experimenter simply "takes the data as it comes".

  3. Binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Binomial_distribution

    In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own Boolean-valued outcome: success (with probability p) or failure (with probability q = 1 − p).

  4. Relationships among probability distributions - Wikipedia

    en.wikipedia.org/wiki/Relationships_among...

    If n and m are large compared to N, and p = m/N is not close to 0 or 1, then X approximately has a Binomial(n, p) distribution. X is a beta-binomial random variable with parameters (n, α, β). Let p = α/(α + β) and suppose α + β is large, then X approximately has a binomial(n, p) distribution.

  5. Binomial test - Wikipedia

    en.wikipedia.org/wiki/Binomial_test

    The binomial test is useful to test hypotheses about the probability of success: : = where is a user-defined value between 0 and 1.. If in a sample of size there are successes, while we expect , the formula of the binomial distribution gives the probability of finding this value:

  6. Poisson binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Poisson_binomial_distribution

    Download as PDF; Printable version; In other projects ... In probability theory and statistics, the Poisson binomial distribution is the discrete probability ...

  7. Binomial process - Wikipedia

    en.wikipedia.org/wiki/Binomial_process

    In these point processes, the number of points is not deterministic like it is with binomial processes, but is determined by a random variable . Therefore mixed binomial processes conditioned on K = n {\displaystyle K=n} are binomial process based on n {\displaystyle n} and P {\displaystyle P} .

  8. De Moivre–Laplace theorem - Wikipedia

    en.wikipedia.org/wiki/De_Moivre–Laplace_theorem

    Within a system whose bins are filled according to the binomial distribution (such as Galton's "bean machine", shown here), given a sufficient number of trials (here the rows of pins, each of which causes a dropped "bean" to fall toward the left or right), a shape representing the probability distribution of k successes in n trials (see bottom of Fig. 7) matches approximately the Gaussian ...

  9. Beta negative binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Beta_negative_binomial...

    In probability theory, a beta negative binomial distribution is the probability distribution of a discrete random variable equal to the number of failures needed to get successes in a sequence of independent Bernoulli trials.

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