Skip to main content

Binomial distribution


Binomial Distribution

Probability Mass FunctionThe binomial distribution is used when there are exactly two mutually exclusive outcomes of a trial. These outcomes are appropriately labeled "success" and "failure". The binomial distribution is used to obtain the probability of observing x successes in N trials, with the probability of success on a single trial denoted by p. The binomial distribution assumes that p is fixed for all trials.The formula for the binomial probability mass function is
P(x,p,n) = (n x)*(p**x)*(1-p)**(n-x) for x = 0, 1, 2, ..., n
where
(n x) = n!/(x!(n-x)!
The following is the plot of the binomial probability density function for four values of p and n = 100.
plot of the binomial probability density function
Cumulative Distribution FunctionThe formula for the binomial cumulative probability function isF(x,p,n) = SUM[(n i)*(p**i)*(1-p)**(n-i)
   where the summation is over i from 0 to x
The following is the plot of the binomial cumulative distribution function with the same values of p as the pdf plots above.
plot of the binomial cumulative distribution function
Percent Point FunctionThe binomial percent point function does not exist in simple closed form. It is computed numerically. Note that because this is a discrete distribution that is only defined for integer values of x, the percent point function is not smooth in the way the percent point function typically is for a continuous distribution.The following is the plot of the binomial percent point function with the same values of p as the pdf plots above.
plot of the binomial percent point function
Common Statistics
Meann*p
Modep*(n+1) - 1 <= x <= p*(n+1)
Range0 to N
Standard DeviationSQRT(n*p*(1-p))
Coefficient of VariationSQRT((1-p)/(n*p))
Skewness(1-2*p)/SQRT(n*p*(1-p))
Kurtosis3 - 6/n + 1/(n*p*(1-p))
CommentsThe binomial distribution is probably the most commonly used discrete distribution.
Parameter EstimationThe maximum likelihood estimator of p (n is fixed) isptilde = x/n
SoftwareMost general purpose statistical software programs support at least some of the probability functions for the binomial distribution.

Comments

Popular posts from this blog

Methods of correlation

Correlation Methods  Correlation and Covariance Matrices Fisher's  z  Transformation ( z r ) Pearson Product-Moment Correlation Coefficient (Pearson's  r ) Spearman's Rank-Order Correlation Coefficient (Spearman's ρ) Kendall's Rank Correlation Coefficient (Kendall's τ) Correlation and Covariance Matrices You can generate a correlation or covariance matrix from numeric data columns, and have the choice of storing the computation results in an-autogenerated worksheet, or display the results in a table format whose values can be color coded. This method requires multiple numeric data columns whose values should be stored in a single worksheet. An example of a correlation matrix displayed as a color-coded table is shown below. Using Fisher's  z  Transformation ( z r ) This option is provided to allow transforming a skewed sampling distribution into a normalized format. The theoretical sampling distribution of the corr...

The most femiliar statisticians

Gertrude Cox :   Gertrude Mary Cox (of Experimental Statistics at North Carolina State University. She was later appointed director of both the Institute of Statistics of 1900 - 1978) was an influential American statistician and founder of the department the Consolidated University of North Carolina and the Statistics Research Division of North Carolina State University. Her most important and influential research dealt with experimental design; she wrote an important book on the subject with W. G. Cochran. In 1949 Cox became the first female elected into the International Statistical Institute and in 1956 she was president of the American Statistical Association. From 1931 to 1933 Cox undertook graduate studies in statistics at the  University of California at Berkeley , then returned to Iowa State College as assistant in the Statistical Laboratory. Here she worked on the  design of experiments . In 1939 she was appointed assistant professor of statisti...

Cauchy distribution

Cauchy Distribution Probability Density Function The general formula for the  probability density function  of the Cauchy distribution is where  t  is the  location parameter  and  s  is the  scale parameter . The case where  t  = 0 and  s  = 1 is called the  standard Cauchy distribution . The equation for the standard Cauchy distribution reduces to Since the general form of probability functions can be  expressed in terms of the standard distribution , all subsequent formulas in this section are given for the standard form of the function. The following is the plot of the standard Cauchy probability density function. Cumulative Distribution Function The formula for the  cumulative distribution function  for the Cauchy distribution is The following is the plot of the Cauchy cumulative distribution function. Percent Point Function The formula for the  percent point function  of...