TITLE:
Derivation of Gaussian Probability Distribution: A New Approach
AUTHORS:
A. T. Adeniran, O. Faweya, T. O. Ogunlade, K. O. Balogun
KEYWORDS:
De Moivres Laplace Limit Theorem, Binomial Probability Mass Function, Gaussian Distribution, Random Experiment
JOURNAL NAME:
Applied Mathematics,
Vol.11 No.6,
June
1,
2020
ABSTRACT: The famous de Moivre’s Laplace limit theorem proved the probability density function of Gaussian distribution from binomial probability mass function under specified conditions. De Moivre’s Laplace approach is cumbersome as it relies heavily on many lemmas and theorems. This paper invented an alternative and less rigorous method of deriving Gaussian distribution from basic random experiment conditional on some assumptions.