若干概率分佈的正態逼近
摘 要
在整個概率論與數理統計中,各種分佈起了重要的作用,其中以正態分佈最爲重要.許多重要的概率分佈都與正態分佈密切相關;此外,很多重要分佈的.極限分佈,在1定條件下也都是正態分佈;有些隨機變量其分佈雖然未知,但是隻要滿足很1般的條件,其極限分佈也是正態分佈.本文主要介紹了若干概率分佈的正態逼近,探討了他們的應用,充分說明正態分佈在概率統計中的重要地位.
關鍵詞：常用分佈；特徵函數；正態逼近；正態逼近的應用
The normal approximation of some probability
ABSTRACT
Various kinds of distribution have played a very important role in the whole probability theory, among them it is most important to regard normal distribution as.a lot of important important probability distribution all have something to do with normal distribution; In addition, a lot of important limit distributed is distributed, are all normal distribution under certain condition; Some random probability distribution of variable unknown even, must meet general terms very, it is normal distribution too that its limit is distributed. In my this paper, i introduce the normal approximation of some probability, and discuss the application of them to speak volumes for the important status in the probability statistics of normal distribution.
Key word:The typic Distribution; Eigenfunction; Normal approximation; The application of the normal approximation
目 錄
中文標題---------------------------------------------------------------------1
中文摘要﹑關鍵詞-------------------------------------------------------------1
英文標題---------------------------------------------------------------------1
英文摘要﹑關鍵詞--------------------------------------------------------------1
正文-------------------------------------------------------------------------2
§1 引言---------------------------------------------------------------------2
§2 常用分佈-----------------------------------------------------------------2
§3 常用分佈的正態逼近--------------------------------------------------------4
§4 在近似計算中的應用-------------------------------------------------------13
§5 其他應用舉例 ------------------------------------------------------------15
§6 結束語 ------------------------------------------------------------------22
參考文獻 -------------------------------------------------------------------23
致謝------------------------------------------------------------------------24
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