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  • Ok, correlations and causation footnotes: In the main video I said that when you find

    好了,關聯性和因果關係腳註。在主視頻中,我說,當你發現。

  • a correlation, it's natural to look for explanations or causes of it. This is called Reichenbach's Principle.

    相關性,就自然而然地要尋找解釋或原因。這就是所謂的 "萊辛巴赫原理"。

  • But sometimes correlations occur just by chance, like those on the websitespurious correlations

    但有時相關性的發生只是偶然的,比如網站上的 "虛假相關性"

  • which selectively cherry-picks data points from different stats that randomly happen

    它有選擇地從隨機發生的不同統計中挑選數據點。

  • to line up.

    來排隊。

  • As an example of a chance correlation, if I flip two coins enough times, eventually

    作為一個偶然相關的例子,如果我拋出兩枚硬幣的次數足夠多,最終

  • there'll be a long string of matching heads or tails just by chance, and if I just cherrypick

    偶然會有一長串的頭尾相配,如果我只是隨便挑一挑的話

  • those flips I can make it look like the coins are super correlated.

    這些翻轉,我可以讓它看起來像硬幣是超級相關的。

  • But when an apparent correlation is actually random in origin (like in this case), then

    但是,當表面上的相關性實際上是隨機的(就像這種情況),那麼

  • if you keep looking at larger and larger samples, the correlation should go away.

    如果你繼續觀察越來越大的樣本,相關性應該會消失。

  • This is it sometimes looks like particle physicists have discovered a new particle, only for that

    這就是它有時看起來像粒子物理學家發現了一種新的粒子,只為這一點。

  • to go away when they collect more data.

    當他們收集更多的數據時,就會消失。

  • Also, you may have noticed there was no mention of feedback loops in the main videothat's

    另外,你可能已經注意到,在主視頻中沒有提到反饋迴路--那是

  • because, from a causal point of view, feedback loops, like how more grass means more sheep

    因為,從因果關係來看,反饋循環,就像草越多意味著羊越多一樣。

  • means less grass means less sheep means more grass and so onfrom a causal point of

    草少意味著羊少意味著草多,以此類推--從因果關係來看

  • view, this isn't actually a loop.

    觀點,這其實不是一個循環。

  • It's more of a chain, where the amount of grass and sheep now affect the amounts of

    更多的是一個鏈條,現在草和羊的數量會影響到的數量。

  • grass and sheep next year, and the year after and so on, so from year to year there's

    草和羊,明年,後年,以此類推,所以年年都有

  • feedback between the amount of grass and the amount of sheep which we kind of draw as a

    草的數量和羊的數量之間的反饋,我們有點畫地為牢。

  • loop, but the causal relationship always goes from the present to the future, which we should

    循環,但因果關係總是從現在到未來,我們應

  • draw as some sort of spirally helix thing.

    畫成某種螺旋狀的螺旋物。

Ok, correlations and causation footnotes: In the main video I said that when you find

好了,關聯性和因果關係腳註。在主視頻中,我說,當你發現。

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B1 中級 中文 反饋 數量 循環 關係 粒子 硬幣

誤區 腳註 †:隨機性和反饋 (Misconceptions Footnote †: Randomness and Feedback)

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    Summer 發佈於 2021 年 04 月 01 日
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