【正文】 d normal curve, so people have attributed the origin of the normal distribution of gambling problems, but because of social and personal problems, the normal curve at that time did not have a great development. The second stage is the mid18th century the normal distribution model, the stimulation of the development of astronomy, mathematician Laplace, Gaussian normal distribution has a new development, so that people e to realize that its in astronomy, application error field. The third stage in the mid19th century Quetelet, Galton’s efforts to make the normal into the natural and scientific fields, from entering the family statistics. Finally, the paper summarizes some of the most basic and normal stage of practical application.【 Keywords】 Normal distribution Moivre Laplace Gauss Kettle 東?？茖W(xué)技術(shù)學(xué)院畢業(yè)論文 III 目 錄 摘 要 ............................................................................................................................... I Abstract............................................................................................................................. II 1 緒論 .............................................................................................................................1 正態(tài)分布的定義 .................................................................................................1 正態(tài)分布的曲線 ..................................................................................................1 正態(tài)分布與標(biāo)準(zhǔn)正態(tài)分布 ..................................................................................2 ...........................................................................................................3 2． 1 古典統(tǒng)計(jì)時(shí)期的概率論 ..................................................................................3 2． 2 二項(xiàng)式正態(tài)逼近 —— 狄莫弗 ..........................................................................4 2． 3 為何當(dāng)時(shí)正態(tài)分布未能有大發(fā)展 ..................................................................4 ...................................................................................................6 3． 1 天文中的誤差 ..................................................................................................6 3． 2 誤 差論的形成 ..................................................................................................6 3． 2． 1 拉普拉斯的概率論 .............................................................................7 3． 2． 2 高斯分布 .............................................................................................7 3． 3 基本誤差假設(shè) ...................................................................................................8 .......................................................................................9 4． 1“近代統(tǒng)計(jì)學(xué)之父” — 凱特萊 ........................................................................9 4． 2 凱特萊對(duì)正態(tài)曲線的拓展 ............................................................................10 4． 3 高爾頓對(duì)正態(tài)分布的創(chuàng)新 .............................................................................10 5. 現(xiàn)代統(tǒng)計(jì)學(xué)中的正態(tài)分布 .......................................................................................12 .........................................................................................................13 頻數(shù)分布 ...........................................................................................................13 對(duì)學(xué)生的一些情況進(jìn)行調(diào)查 ...........................................................................13 醫(yī)學(xué)的正常值范圍參考 ...................................................................................17 正態(tài)分布促進(jìn)統(tǒng)計(jì)學(xué)的發(fā)展 ...........................................................................17 .結(jié)束語(yǔ) ...........................................................................................................................19 參考文獻(xiàn) .........................................................................................................................20 東海科學(xué)技術(shù)學(xué)院畢業(yè)論文 1 1 緒論 若隨機(jī)變量 x 服從一個(gè)位置參數(shù)為 ? ，尺度函數(shù)為 ? ，其概率密度函數(shù)為? ?