Open AccessApproximation of the Binomial Probability Function Using the Discrete Normal Distribution
Author(s) -
Mohammad Fraiwan Al-Saleh,
Doaa Suhail Obeidat
Publication year - 2022
Publication title -
international journal of statistics and probability
Language(s) - English
Resource type - Journals
eISSN - 1927-7040
pISSN - 1927-7032
DOI - 10.5539/ijsp.v11n3p32
Subject(s) - mathematics , binomial approximation , binomial distribution , probability distribution , negative binomial distribution , probability mass function , binomial (polynomial) , limit (mathematics) , characteristic function (probability theory) , measure (data warehouse) , central limit theorem , approximation error , statistics , probability density function , mathematical analysis , computer science , poisson distribution , database
A new method of approximating the Binomial probability function is introduced. The method is based on the discrete normal distribution. In particular, the discrete normal probability function is used to approximate the binomial probability function. The new approximation is compared with the exact values and the approximation based on Central limit theorem. The maximum absolute error of the approximation is used to measure the accuracy of the method. It turned out that this method of approximation is useful and easy to use in practice. Also, the result can be an important theoretical statistical result that can be used in educational statistics.