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    # 教育統計1103 ###### tags: `教育統計學` 課前講解: 盡量在LINE上討論作業與小考,不然課程內容很多會教不完 [彼西量表](https://pedia.cloud.edu.tw/Entry/Detail/?title=%E6%AF%94%E8%A5%BF%E9%87%8F%E8%A1%A8) 做一個學生要1.5小時,早期老師投入大量時間研究 百分等級一定要是**整數**。(定義) 所以課本60頁 $PR\ 99.6$ $\Rightarrow$ $PR\ 99^+$ $PR\ \ \ 0.4$ $\Rightarrow$ $PR\ \ \ 1^-$ 其他四捨五入 (沒有零沒有100) 建常模一定要找性質接近的,一定是屬於數組中的一份子 因此不可能出現$PR=100$ 或是 $PR=0$ 原始分數不一樣,百分等級是可能有一樣的 (博文:或許用五科考試總分百分等級應該蠻容易理解?) 百分等級屬於次序變數 --- ### [標準分數](https://pedia.cloud.edu.tw/Entry/Detail/?title=%E6%A8%99%E6%BA%96%E5%88%86%E6%95%B8) 標準分數可以告訴我們某一分數在團體平均數之上或之下多少標準差 有非常多種,是一個通稱 #### Z分數 $Z=\dfrac{X-\bar X}{S}$ 手寫時寫成書寫體Z比較好,這樣才能跟小寫z做區分 ![](https://i.imgur.com/YwUr7F5.jpg) 這個公式很重要,以後常常會用,所以一定要記 Z是無名數(沒有單位數值) $S應該寫成S_x$(第七章之後就會用到) 使用標準差 各科總分相加本身是不合邏輯的,理論上應該先轉換成標準分數才能比較與相加。 因為原始分數嚴格來說是次序變數(準等距變數),要轉成Z分數才是等距變數 ##### Z分數特性 * 平均數為0,變異數及標準差為1 * 小於平均數者Z值為負,反之為正 * $\Sigma Z^2 =N$ * Z為原始分數的直線轉換,$Z=aX+b$;$a=\dfrac{1}{S}$;$b=-\dfrac{\bar X}{S}$ 其他標準分數多為Z之直線轉換, (為避免平均數為0,帶有小數與負號的Z值等問題) [T分數](https://www.exam.gov.tw/News_Content.aspx?n=3435&s=24952) = $T=10Z+50$ 一定要寫大寫T T 分數是教育統計學名詞,為莫考兒(W.A. McCall)所創,為尊崇心理學家桑代克(E.L. Thorndike)及特門(L.M. Terman)二氏,故取其姓氏第一字母 T,命名為T分數。 因此人名一定要大寫 [美國陸軍分類測驗AGCT ](https://pedia.cloud.edu.tw/Entry/Detail/?title=%E9%99%B8%E8%BB%8D%E6%99%AE%E9%80%9A%E5%88%86%E9%A1%9E%E6%B8%AC%E9%A9%97)= $20Z+100$ 美國大學入學考試CEEB = $100Z+50$ 彼西量表、魏式測驗等也都是Z直線轉換 ### 百分等級與標準分數比較 * 百分等級較易理解 * 百分等級為次序變數,不適合作運算 * 標準分數為等距量尺,適合數學處理 * 標準分數一般人不易理解 * 各有優缺,因此有時會並行 --- 回顧: CH1 2 變數與類別,其中次數多邊圖會用到最多 CH3 4 資料的集中情形如何,如何用統計來表達,分散的情況如何 CH5 相對地位量數,每個數組的好壞優劣,是教育統計重要的一章 一個多邊圖有四個要探討,偏態,集中情形等,但沒有專章在講峰度 重要性較低所以放在CH6 分節來講。因為與第六章有所關聯 盡信書不如無書,以林清玄為例 但不用完全否定書,詳細請上課多聽老師講的改正之處。 ## 常態分配 * 非常難出現完美常態分配 * 左右對稱鐘形分配 P68 圖6-1 沒有缺口,連續變數所以可以畫成次數分配圖。 P68 圖6-2 機率**次數**不是連續變數,所以應該轉呈長條圖,不能連在一起, 二項分配,其變數只有YES/NO兩種 是n個獨立的是/非試驗中成功的次數的離散機率分布 ![](https://i.imgur.com/afgsHYl.jpg) 作者試圖想要用二項分配,N極大時很像常態分配,但到底他還是長條圖,不相連。因此不合理 常態分配又是一種高斯分配 ### 常態分配的特性 $\sigma$ = 母群體標準差,念作sigma $\mu$ = 母群體平均數,念作mu 謬 * X一定要是連續變數 * 對稱於$X=\mu$ * 平均數=中數=眾數 * 反曲點在$X=\mu -\sigma 或X=\mu +\sigma$ * 曲線向左右兩端逐漸降低,左右兩端與橫軸為**漸近線** * **曲線下面積為1** * $\sigma^2$不變, $\mu$改變,則位置不同但**形狀相同**,$\sigma^2$改變, $\mu$不改變,則位置不變,形狀改變。 一般數組很難符合所有條件。 ### 標準常態分配 轉成標準分數, 於是公式可以轉成$Y=\dfrac{1}{\sqrt {2\pi}}e^{-\dfrac{z^2}{2}}$ 好處是轉換成Z之後,不論哪種常態分配表都是一樣的,可以使用查表法 **先決條件:曲線下面積為1** 積分等都可以快速查表得到面積。 因此只要建一個表就可以通用了 圖6-4畫錯 轉成Z值應該是相等的(因為Z為**直線轉換,永遠圖形不會變**) 其實應該是X軸單位換了(根本是不同的圖) 標準常態分配 * 對稱於Z=0,為最高點,Y=.3989 * |Z|>3,Y已經很小了,與橫軸為**漸近線** * 曲線下面積為1 * 平均數0,標準差1 P444頁查表 機率為到Z=0之面積 Z=1 機率為 .3413 這類面積計算宜畫圖輔助思考 ### 標準常態曲線下之面積 常用數字 Z=1.65 $\rightarrow$ .05 Z=1.96 $\rightarrow$ 95% Z=2.58 $\rightarrow$ 99% Z=2.33 $\rightarrow$ .01 通常不會需要精準到兩位以下,因為拒絕虛無假設與否很少遇到剛好在分界點上,有需要可以用內差法或是找更精確的表 ![](https://i.imgur.com/6Qh2Zov.jpg) ### 偏態與峰度 偏度與峰度公式 一般用動差(moment)計算 一級類似平均數、二級類似變異數 非常少用,所以不用特地去記憶 講義上的偏度例外 一看即不是對稱,但$G_1$ 為0 ![](https://i.imgur.com/KOqOSks.jpg) ![](https://i.imgur.com/3rCsz3A.jpg) 峰度例外,低的圖反而峰度較高 ![](https://i.imgur.com/Lkg45Tg.jpg) ### 次數分配的常態化(跳過) 使用機會太低 ### 常態分配下各種分數之比較(先回去看,下次講) ___ 小考開始

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