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Derivation of Gaussian Probability Distribution: A New Approach
Department of Statistics, University of Ibadan, Ibadan, Nigeria
Department of Statistics, Ekiti State University (EKSU), Ado-Ekiti, Nigeria
Department of Mathematics, Ekiti State University (EKSU), Ado-Ekiti, Nigeria
Department of Statistics, Federal School of Statistics, Ibadan, Nigeria
- 1 Department of Statistics, University of Ibadan, Ibadan, Nigeria
- 2 Department of Statistics, Ekiti State University (EKSU), Ado-Ekiti, Nigeria
- 3 Department of Mathematics, Ekiti State University (EKSU), Ado-Ekiti, Nigeria
- 4 Department of Statistics, Federal School of Statistics, Ibadan, Nigeria
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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.
KeywordsDe Moivres Laplace Limit TheoremBinomial Probability Mass FunctionGaussian DistributionRandom Experiment
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