Distinguishing the signal from the noise requires both scientific knowledge and self-knowledge: the serenity to accept the things we cannot predict, the courage to predict the things we can, and the wisdom to know the difference.
There's always the risk that there are unknown unknowns.
The signal is the truth. The noise is what distracts us from the truth.
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 out the useful information from all this noise.
Data scientist is just a sexed up word for statistician.
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 represent signal or noise
We must become more comfortable with probability and uncertainty.
When a possibility is unfamiliar to us, we do not even think about it.
New ideas are sometimes found in the most granular details of a problem where few others bother to look.
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 more of our data, we need to demand more of ourselves.
Success makes you less intimidated by things.
We need to stop, and admit it: we have a prediction problem. We love to predict things—and we aren’t very good at it.
When human judgment and big data intersect there are some funny things that happen
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 is increasing, the gap between what we know and what we think we know may be widening.
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, right? But most of it is like cat videos on YouTube or thirteen-year-olds exchanging text messages about the next 'Twilight' movie.
We speak for them. We imbue them with meaning.
A lot of news is just entertainment masquerading as news.
People gravitate toward information that implies a happier outlook for them.
Well the way we perceive accuracy and what accuracy is statistically are really two different things.
The quest for certainty in forecasting outcomes can be the enemy of progress.
On average, people should be more skeptical when they see numbers. They should be more willing to play around with the data themselves.
Economy is not baseball, where the game is always played by the same rules.
Distinguishing the signal from the noise requires both scientific knowledge and self-knowledge.
By playing games you can artificially speed up your learning curve to develop the right kind of thought processes.
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.
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