Probability Laws Derived from the Euler Gamma Function: Understanding through Case Studies | Chapter 1 | Mathematics and Computer Science: Contemporary Developments Vol. 4

Several densities or probability laws of continuous random variables derive from the Euler Gamma function. These laws form the basis of sampling theory, namely hypothesis testing and estimation. Namely the gamma, beta, and Student law, through the chi-square law and the normal law are all distributions resulting from applications of Euleur functions. Application of the functions of Euler contributed to and facilitated the obtaining of important results in statistics and especially in the theories of distribution of sampling. Several densities or probability laws of continuous random variables derive from the Euler Gamma function. These laws form the basis of sampling theory, namely hypothesis testing and estimation. This study aims to understand the Euler Gamma Function and its associated laws of probabilities or probability distributions derived from the function gamma. Namely the gamma, beta, and Student law, through the chi-square law and the normal law are all distributions resulting from applications of Euler functions.

 

Author (s) Details

Lansana Toure
Department of Business Administration and LaboMaths, University Julius Nyéréré of Kankan, Kankan, Guinea.

Soumaila Conde
Faculty of Sciences, University Julius Nyéréré of Kankan, Kankan, Guinea.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/mcscd/v4/3688G