April 2014
Beginner to intermediate
830 pages
15h 21m
Chinese
Content preview from Mathematica 錦囊妙計
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12.12 以類別型資料（Categorical Data）進行假設檢定（Hypothesis Testing）
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483
討論說明
ChiSquarePValue
指令的第二個引數為分布自由度。毋庸置疑地，前述範例的自由度為
1，RC 資料的自由度定義為（列數 -1）（行數 -1）。[Page-485]
文獻中常見一些表格，列出不同分布的臨界值與顯著程度 alpha（α）的對應關係。例
如：當 α 為 0.05 時，表示有 95% 的信賴水準，換言之，為（1-α）* 100%。前述範例
中，特定自由度的臨界值來自所需信賴程度的卡方值下限（或上限），臨界值的計算即
是找出 PDF 曲線下的面積為 α 時的條件，使用
FindRoot
與
NIntegrate
指令可以迅速
求得 α。
下式求得前述範例 α 為 0.05 時，其臨界值 c 為何。
範例中的卡方值為 45.47，明顯高於上值，因此推翻虛無假設。若卡方值低於臨界下限
也是可以接受的，但很明顯的本例中並不成立。
用相同方法你可以自行建立自由度與臨界值的表格，類似的表格你可以在「延伸資料」
中找到。
ch12.indd 483 2014/4/2 下午 01:57:56
484
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第十二章
延伸資訊
關於卡方檢定的更多資訊，請參考由美國國家標準與技術局（NI
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