The signal is the truth. The noise is what distracts us from the truth..

On average, people should be more skeptical when they see numbers. They should be more willing to play around with the data themselves..

One of the pervasive risks that we face in the information age, as I wrote in the introduction, is that even if the amount of knowledge in the world ….

People gravitate toward information that implies a happier outlook for them..

We speak for them. We imbue them with meaning..

Every day, three times per second, we produce the equivalent of the amount of data that the Library of Congress has in it's entire print collection, ….

We're not that much smarter than we used to be, even though we have much more information - and that means the real skill now is learning how to pick….

Data-driven predictions can succeed-and they can fail. It is when we deny our role in the process that the odds of failure rise. Before we demand mor….

Economy is not baseball, where the game is always played by the same rules..

A lot of news is just entertainment masquerading as news..

When human judgment and big data intersect there are some funny things that happen.

Distinguishing the signal from the noise requires both scientific knowledge and self-knowledge: the serenity to accept the things we cannot predict, ….

New ideas are sometimes found in the most granular details of a problem where few others bother to look..

The quest for certainty in forecasting outcomes can be the enemy of progress..

Finding patterns is easy in any kind of data-rich environment; that's what mediocre gamblers do. The key is in determining whether the patterns repre….

When a possibility is unfamiliar to us, we do not even think about it..

Well the way we perceive accuracy and what accuracy is statistically are really two different things..

We must become more comfortable with probability and uncertainty..

People don't have a good intuitive sense of how to weigh new information in light of what they already know. They tend to overrate it..

Data scientist is just a sexed up word for statistician..

There's always the risk that there are unknown unknowns..