A Quote by Charlie Munger

Don't confuse correlation and causation. Almost all great records eventually dwindle. — © Charlie Munger
Don't confuse correlation and causation. Almost all great records eventually dwindle.
I'm very familiar with how people can confuse correlation with causation.
If ... we choose a group of social phenomena with no antecedent knowledge of the causation or absence of causation among them, then the calculation of correlation coefficients, total or partial, will not advance us a step toward evaluating the importance of the causes at work.
Correlation is not causation.
All too often when liberals cite statistics, they forget the statisticians' warning that correlation is not causation.
I have never been in a bad mood and near a beach ball at the same time. Causation? Correlation? Or fate?
Correlation doesn’t imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing ‘look over there.’
We should be cautious about embracing data before it is published in the academic press, and must always avoid treating correlation as causation.
The big mystery of Big Data is causation versus correlation.
While our energy efficiency is improving, there is a very high correlation, almost near perfect correlation, between GDP growth, and energy usage.
I will not concede for a moment that old privileges should not dwindle. They cannot dwindle fast enough.
Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.
Those who use 'Correlation is not the same as causation' as a magic incantation to dismiss all fact-using professions are fools holding a lit match in one hand and an open gas can in the other, screaming, 'One has nothing to do with the other!'
There is an excellent correlation between giving society what it wants and making money, and almost no correlation between the desire to make money and how much money one makes.
Big data is great when you want to verify and quantify small data - as big data is all about seeking a correlation - small data about seeking the causation.
To my knowledge there are no good records that have been built by institutions run by committee. In almost all cases the great records are the product of individuals, perhaps working together, but always within a clearly defined framework. Their names are on the door and they are quite visible to the investing public. In reality outstanding records are made by dictators, hopefully benevolent, but nonetheless dictators.
Men need to be aware of the health of their bodies, as well - prostate cancer and breast cancer are almost on the same level. It's fascinating to me that the correlation between the two is almost the same - people don't talk about it so much, but they are almost equal in numbers.
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