September 2013
Intermediate to advanced
264 pages
5h
Chinese
Content preview from Bad Data 技術手冊
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第十一章：別讓「完美」成為「好」的敵人：壞資料真的壞嗎？
為了要在一個不完美的資料環境中，作出明智的策略與戰略性的決定，必須要妥協。從
學術的觀點來看，這些妥協不太合理。我們正在拋棄分析的品質，並且遵守研究的標
準。然而，我必須重複的說，寧願在不完美的資料上做出明智的決策，也不要在沒有任
何資料的狀況下作決策。當我們接受了這個不完美，便能夠打開整合資料到所有支援的
專案與政策的能力。在決定中擁有漸增收益的能力，很可能會導致政策的實質改善。
我相信在標準研究與實際現實之間是有空間的。傳統的研究需要嚴謹且結構的統計測試
來隨機的挑選樣本。現實則無法總是讓我們隨機挑選樣本，而通常從生態系而來的資料
並不會達到所有需要的假設。也就是說，這並不是在絕對準確與完全不準之間的選擇，
反而是個延伸我們的工具的機會，讓這些工具用在典型的「黃金標準」之外。
向前邁進
向前邁進，政府在我們定義應該要如何使用資料時，需要走得更小心。我們需要謹記過
去所學到的經驗。特別是，有兩個領域特別常產生問題：
害怕學術界。傳統上，學術界是某些頂尖資料研究者的家，並且吸收科學界的問題。儘
管這樣可能會產生黃金標準的研究，但它通常會伴隨著兩個相關聯的考量。這類詳細且
受控制的研究速度通常會較慢。花數年來取得資料與分析它，對一個想要執行聰明策略
性政策的靈敏政府來說並沒有幫助。
害怕令人驚奇的結果。在這種狀況中，評估者會先開始審查，然後在幾天後會對世界宣
佈這是一個失敗且毫無價值的研究。這是一個非常正當的考量。長的時限並不會讓政
府在短期內做得更好 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.