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Data Science from Scratch中文版|用Python學資料科學
book

Data Science from Scratch中文版|用Python學資料科學

by Joel Grus
October 2016
Beginner to intermediate
328 pages
6h 58m
Chinese
GoTop Information, Inc.
Content preview from Data Science from Scratch中文版|用Python學資料科學
92
第七章:假設與推論
7-2
從不同的先驗分布,所得出的後驗分布
有趣的是,這種做法讓我們可以對假設做出機率性的陳述:「根據先驗分布與觀測數
據,只有 5% 的可能性,硬幣出現正面機率會落在 49% 51% 之間。」這在哲學上來
說,與以下的陳述有很大的不同:「如果硬幣是公正的,我們就可以預期只有 5% 的機
率出現如此極端的觀測數據。」
運用貝氏推論來進行假設的檢定,這種做法其實還是頗受爭議,部分原因是因為所牽
涉到的數學相當複雜,還有部分原因是因為在選擇先驗分布時存在著一定的主觀性。
我們在本書中並不會進一步運用到這種做法,但你還是知道一下比較好。
進一步探索
y
關於我們應該瞭解的統計推論知識,本章只是接觸到一點皮毛而已。本書第 5
最後推薦的一些書籍,可以讓你深入更多的細節。
y
Coursera 論(
https://www.
coursera.org/course/statistics
)相關的課程,內容涵蓋許多關於這方面的主題。
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Publisher Resources

ISBN: 9789864761982