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Causation Quotes

Tracing cause and effect across science and data.

These causation quotes move from Darwin's work on evolution to broader reflections on how science traces cause and effect back to first principles. One line frames all scientific unity as ultimately connected through a chain of causation.

Agricultural practice served Darwin as the material basis for the elaboration of his theory of Evolution, which explained the natural causation of the adaptation we see in the structure of the organic world. That was a great advance in the...

Quotes by Trofim Lysenko

The great unity which true science seeks is found only by beginning with our knowledge of God, and coming down from Him along the stream of causation to every fact and event that affects us.

Quotes by Howard Crosby

From the mid-1970s, I also started work on the causation and prevention of famines.

Quotes by Amartya Sen

The big mystery of Big Data is causation versus correlation.

Quotes by Alexander Nix

Frequently Asked Questions

How does Darwin connect to these causation quotes?
One quote credits agricultural practices as material Darwin used to help explain the natural causation behind evolutionary adaptation.
Is there a quote linking causation to religion or science?
Yes, one describes true scientific unity as something found by tracing causation back through a chain, starting from knowledge of God.
Do any quotes mention famine research?
One references work starting in the mid-1970s focused specifically on understanding the causes and prevention of famines.
What's the Big Data quote about?
It points out that a central challenge with large datasets is distinguishing genuine causation from mere correlation between events.
Why does the difference between causation and correlation matter?
Because assuming two related things cause each other, rather than just appearing together, can lead to flawed conclusions, a mistake this collection highlights more than once.

More applied examples follow, including research into what actually causes famines and a modern reminder that with Big Data, mistaking correlation for real causation remains an easy and common mistake.