Quotes About Probability

in the presence of nonlinearities, the longer the forecast the worse its accuracy.

could not understand what made one explanation more likely than the other

Antifragile shows how people confuse risk of ruin with variations and fluctuations—a simplification that violates a deeper, more rigorous logic of things.

as they are hedging the possibility of their falling into the same situation some day.

I wonder why people don't realize the simple truism, that is, the fooled by randomness effect: mistaking the merely associative for the causal, that is, if rich countries are educated, immediately inferring that education makes a country rich, without even checking. Epiphenomenon

Events that are nonrepeatable are ignored before their occurrence, and overestimated after (for a while). After

Every single risk you take adds up to reduce your life expectancy.

extreme event as a starting point and not treat it as an exception to be pushed under the rug.

that even a broken clock is right twice a day.

shows why the convex likes volatility. If you earn more than you lose from fluctuations, you want a lot of fluctuations.

Cancer from smoking seems more likely than cancer without a cause attached to it

Option = asymmetry + rationality

in fact, they are so blind to the odds that they treat odds of one in a thousand and one in a million almost in the same way.

Everything nonstable or breakable has had ample chance to break over time.

blinding people to the odds of success when engaging in ventures.

The notion of future mixed with chance, not a deterministic extension of your perception of the past, is a mental operation that our mind cannot perform.

We learn from repetition—at the expense of events that have not happened before.

he understood optionality mathematically, but not really outside the equation.

notion of alternative accounting: $ 10 million earned through Russian roulette does not have the same value as $ 10 million earned through the diligent and artful practice of dentistry.

It is hard to explain to naive data-driven people that risk is in the future, not in the past.

Mathematicians of probability give that a fancy name: ergodicity. It means, roughly, that (under certain conditions) very long sample paths would end up resembling each other. The properties of a very, very long sample path would be similar to the Monte Carlo properties of an average of shorter ones.

Black Swan logic makes what you don't know far more relevant than what you do know.

that there is no evidence of the possibility of large events, i.e., Black Swans. You are likely to confuse that statement, however, particularly if you do not pay close attention, with the statement that there is evidence of no possible Black

that the Black Swan has three attributes: unpredictability, consequences, and retrospective explainability. Let