An Integral Proof of the Joint M.G.F. of Sample Mean and Variance

Without assuming independence of sample mean and variance, or without using any conditional distribution, we present an integral proof of the joint moment generating function for sample mean and variance for independently, identically and normally distributed random variables. This proves the independence of sample mean and variance which is the basis of Student t-Test and many other inferential methods. IJSS, Vol. 24(2)s (Special Issue), December, 2024, pp 19-23

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Publication Details

Journal
International Journal of Statistical Sciences
Published
2024-12-23
DOI
https://doi.org/10.3329/ijss.v24i20.78211
Primary Topic
Statistical and numerical algorithms
Type
article
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article

An Integral Proof of the Joint M.G.F. of Sample Mean and Variance

A. Laradji, Anwar H. Joarder
International Journal of Statistical Sciences
Statistical and numerical algorithms
article

An Integral Proof of the Joint M.G.F. of Sample Mean and Variance

A. Laradji, Anwar H. Joarder
article en

Abstract

Without assuming independence of sample mean and variance, or without using any conditional distribution, we present an integral proof of the joint moment generating function for sample mean and variance for independently, identically and normally distributed random variables. This proves the independence of sample mean and variance which is the basis of Student t-Test and many other inferential methods. IJSS, Vol. 24(2)s (Special Issue), December, 2024, pp 19-23

International Journal of Statistical Sciences
King Fahd University of Petroleum and Minerals (SA), Al Akhawayn University (MA)
Openalex Percentile: Top 61%
Statistical and numerical algorithms
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