博碩士論文 103225017 完整後設資料紀錄

DC 欄位 語言
DC.contributor統計研究所zh_TW
DC.creator廖昱婷zh_TW
DC.creatorYu-Ting Liaoen_US
dc.date.accessioned2016-8-25T07:39:07Z
dc.date.available2016-8-25T07:39:07Z
dc.date.issued2016
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=103225017
dc.contributor.department統計研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract在應用統計中,使用二項分配近似常態分配使用連續性校正是非常有用的。首先,論文的第一部分,回顧二項分配和中央極限定理。如果樣本數較大,二項分配會近似於常態分配。連續性校正是為了進一步提高二項分配近似常態分配的準確,其中較廣為人知的連續性較正為Yates’s correction for continuity (Yates, 1934; Cox, 1970)。此外我們還介紹比較少人知道的Cressie’s finely tuned continuity correction (Cressie, 1978)。我們將連續性較正應用在統計製程的問題中。此外,我們進行數值模擬研究,比較Yates’s correction for continuity跟Cressie’s finely tuned continuity correction。zh_TW
dc.description.abstractIn applied statistics, the continuity correction is useful when the binomial distribution is approximated by the normal distribution. In the first part of this thesis, we review the binomial distribution and the central limit theorem. If the sample size gets larger, the binomial distribution approaches to the normal distribution. The continuity correction is an adjustment that is made to further improve the normal approximation, also known as Yates’s correction for continuity (Yates, 1934; Cox, 1970). We also introduce Cressie’s finely tuned continuity correction (Cressie, 1978), which are less known for statisticians. We discuss the application of these continuity corrections to the problem of statistical process control and confidence limit. In addition, we perform numerical studies to compare these corrections.en_US
DC.subject二項分配zh_TW
DC.subject信賴界線zh_TW
DC.subject連續性校正zh_TW
DC.subject控制圖zh_TW
DC.subject常態近似zh_TW
DC.subject統計製程管制zh_TW
DC.subjectBinomial distributionen_US
DC.subjectConfidence limiten_US
DC.subjectContinuity correctionen_US
DC.subjectControl charten_US
DC.subjectNormal approximationen_US
DC.subjectStatistical process controlen_US
DC.titleA review and comparison of continuity correction rules: the normal approximation to the binomial distributionen_US
dc.language.isoen_USen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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