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Binomial distribution

Lecture




Binomial distribution
Probability function
  Binomial distribution
Distribution function
Designation   Binomial distribution
Options   Binomial distribution - the number of "tests"
  Binomial distribution - the probability of "success"
Carrier   Binomial distribution
Probability function   Binomial distribution
Distribution function   Binomial distribution
Expected value   Binomial distribution
Median one of   Binomial distribution
Fashion   Binomial distribution
Dispersion   Binomial distribution
Asymmetry coefficient   Binomial distribution
Coefficient of kurtosis   Binomial distribution
Informational entropy   Binomial distribution
Generating function of moments   Binomial distribution
Characteristic function   Binomial distribution

The binomial distribution in probability theory is the distribution of the number of “successes” in a sequence of   Binomial distribution independent random experiments, such that the probability of “success” in each of them is constant and equal   Binomial distribution .

Content

  • 1 Definition
  • 2 distribution function
  • 3 Moments
  • 4 Properties of the binomial distribution
  • 5 Relationship with other distributions
  • 6 See also

Definition [edit]

Let be   Binomial distribution - a finite sequence of independent random variables with the same Bernoulli distribution with the parameter   Binomial distribution that is, with each   Binomial distribution magnitude   Binomial distribution takes values   Binomial distribution ("Success") and   Binomial distribution ("Failure") with probabilities   Binomial distribution and   Binomial distribution respectively. Then a random variable

  Binomial distribution

has a binomial distribution with parameters   Binomial distribution and   Binomial distribution . This is written as:

  Binomial distribution .

Random variable   Binomial distribution usually interpreted as the number of successes in a series of   Binomial distribution identical independent Bernoulli tests with probability of success   Binomial distribution in every test.

The probability function is given by the formula:

  Binomial distribution

Where

  Binomial distribution - Binomial coefficient.

Distribution function [edit]

The distribution function of the binomial distribution can be written as a sum:

  Binomial distribution ,

Where   Binomial distribution denotes the largest integer not exceeding the number   Binomial distribution , or in the form of an incomplete beta function:

  Binomial distribution .

Moments [edit]

The generating function of moments of the binomial distribution is:

  Binomial distribution ,

from where

  Binomial distribution ,
  Binomial distribution ,

and the variance is a random variable.

  Binomial distribution .

Properties of the binomial distribution [edit]

  • Let be   Binomial distribution and   Binomial distribution . Then   Binomial distribution .
  • Let be   Binomial distribution and   Binomial distribution . Then   Binomial distribution .

Relationship with other distributions [edit]

  • If a   Binomial distribution , then, obviously, we obtain the Bernoulli distribution.
  • If a   Binomial distribution large, then by virtue of the central limit theorem   Binomial distribution where   Binomial distribution - normal distribution with expectation   Binomial distribution and variance   Binomial distribution .
  • If a   Binomial distribution great as well   Binomial distribution - fixed number, then   Binomial distribution where   Binomial distribution - Poisson distribution with parameter   Binomial distribution .
  • If random values   Binomial distribution and   Binomial distribution have binomial distributions   Binomial distribution and   Binomial distribution accordingly, the conditional distribution of the random variable   Binomial distribution provided   Binomial distribution - hypergeometric   Binomial distribution .

See also [edit]

created: 2015-01-01
updated: 2021-03-13
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Probability theory. Mathematical Statistics and Stochastic Analysis

Terms: Probability theory. Mathematical Statistics and Stochastic Analysis