The Application of Central Limit Theorem
Abstract
The central limit theorem is a kind of important theorem in the probability theory that the distribution of the sequence of random variables is asymptotically normal. In this paper, we fi rst give some common central limit theorems from the content of the central limit theorem, and then prove the central limit theorem in the supply of electricity, device prices, shopping malls management, cigarette manufacturing, social life, military problem and so on. Finally, the advantages and disadvantages of the central limit theorem are analyzed.Copyright (c) 2022 Qianju Cheng, Zongming Yang, Xifan Lu
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors contributing to the journal agree to publish their articles under the Creative Commons Attribution-Noncommercial 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit, that the work is not used for commercial purposes, and that in the event of reuse or distribution, the terms of this license are made clear.
References
Xie Yongqin. Probability Theory and Mathematical Statistics [M]. Beijing: Beijing University of Posts and Telecommunications
Press, 2009: 18-36.
Wei Wenyuan. Probability theory and mathematical statistics [M]. Tianjin: Tianjin Education Press .2006: 89-94.
Su Chun. Probability theory [M]. Beijing: Science Press, 2010: 34-36.
Gong Yourong. Statistics [M]. Beijing: Mechanical Industry Press, 2004
Yan Keyu. Cigarette smoke chemistry [M]. Zhengzhou: Zhengzhou University Press, 2002.
Ding Zhengsheng. Probability theory and mathematical statistics concise tutorial [M]. Beijing: Higher Education Press, 2005:
-49.
Fan Jincheng, Zhou Jia, Qian Changben. Probability theory [M]. Xi'an: Xi'an Jiaotong University Press .1987: 105-130.
Wei Zongshu. Probability theory and mathematical statistics tutorial [M]. Beijing: Higher Education Press .2008: 45-99.
Song Qinglong. The central limit theorem in the mall management role [J]. Shopping Mall Modernization. 2006, (482): 70-71
Fisher R. A. Theory of statistical estimation. Proceedings of the Cambridge Philosophical Society, 1925 (22): 700-715
Finklestein J A, Byar D P. Percentage points of the asympotic distributions of one and two sample K-S statistics for truncated
or censored data. Technologist, 1975 (17): 507-510
