The Signal and the Noise Quotes

“Absolutely nothing useful is realized when one person who holds that there is a 0 percent probability of something argues against another person who holds that the probability is 100 percent.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“The alchemy that the ratings agencies performed was to spin uncertainty into what looked and felt like risk. They took highly novel securities, subject to an enormous amount of systemic uncertainty, and claimed the ability to quantify just how risky they were. Not only that, but of all possible conclusions, they came to the astounding one that these investments were almost risk-free.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“What makes him successful is the way that he analyzes information. He is not just hunting for patterns. Instead, Bob combines his knowledge of statistics with his knowledge of basketball in order to identify meaningful relationships in the data.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“When we advance more confident claims and they fail to come to fruition, this constitutes much more powerful evidence against our hypothesis. We can't really blame anyone for losing faith when this occurs”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—But Some Don't

“If there is a mutual distrust between the weather forecaster and the public, the public may not listen when they need to most.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—But Some Don't

“How can we apply our judgment to the data—without succumbing to our biases?”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“We are undoubtedly living with many delusions that we do not even realize.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“Political experts had difficulty anticipating the USSR’s collapse, Tetlock found, because a prediction that not only forecast the regime’s demise but also understood the reasons for it required different strands of argument to be woven together. There was nothing inherently contradictory about these ideas, but they tended to emanate from people on different sides of the political spectrum,11 and scholars firmly entrenched in one ideological camp were unlikely to have embraced them both.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“Quite a lot of evidence suggests that aggregate or group forecasts are more accurate than individual ones, often somewhere between 15 and 20 percent more accurate depending on the discipline. That doesn’t necessarily mean the group forecasts are good. (We’ll”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“The leap is into the Bayesian way of thinking about prediction and probability.”
― Nate Silver, The Signal and the Noise: The Art and Science of Prediction

“All models are wrong, but some models are useful.”90 What he meant by that is that all models are simplifications of the universe, as they must necessarily be.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“The litmus test for whether you are a competent forecaster is if more information makes your predictions better.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“The key to making a good forecast, as we observed in chapter 2, is not in limiting yourself to quantitative information. Rather, it’s having a good process for weighing the information appropriately.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“It is much easier after the event to sort the relevant from the irrelevant signals. After the event, of course, a signal is always crystal clear; we can now see what disaster it was signaling, since the disaster has occurred. But before the event it is obscure and pregnant with conflicting meanings. It comes to the observer embedded in an atmosphere of “noise,” i.e., in the company of all sorts of information that is useless and irrelevant for predicting the particular disaster.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“A forecaster who says he doesn’t care about the science is like the cook who says he doesn’t care about food.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“As John Maynard Keynes said, “The market can stay irrational longer than you can stay solvent.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“After adjusting for inflation, a $10,000 investment made in a home in 1896 would be worth just $10,600 in 1996.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“Human beings have an extraordinary capacity to ignore risks that threaten their livelihood, as though this will make them go away.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“We may, without even realizing it, work backward to generate persuasive-sounding theories that rationalize them, and these will often fool our friends and colleagues as well as ourselves.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“What a well-designed forecasting system can do is sort out which statistics are relatively more susceptible to luck; batting average, for instance, is more erratic than home runs.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“In any contentious debate, some people will find it advantageous to align themselves with the crowd, while a smaller number will come to see themselves as persecuted outsiders. This may especially hold in a field like climate science, where the data is noisy and the predictions are hard to experience in a visceral way. And it may be especially common in the United States, which is admirably independent-minded.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—But Some Don't

“The Industrial Revolution largely began in Protestant countries and largely in those with a free press, where both religious and scientific ideas could flow without fear of censorship.25”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“Alvin Toffler, writing in the book Future Shock in 1970, predicted some of the consequences of what he called “information overload.” He thought our defense mechanism would be to simplify the world in ways that confirmed our biases, even as the world itself was growing more diverse and more complex.42”
― Nate Silver, The Signal and the Noise: The Art and Science of Prediction

“Some of you may be uncomfortable with a premise that I have been hinting at and will now state explicitly: we can never make perfectly objective predictions. They will always be tainted by our subjective point of view.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—But Some Don't

“In Bayesland, you must make one of these two choices: come to a consensus or bet.* Otherwise, to a Bayesian, you are not really being rational.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“If you can’t make a good prediction, it is very often harmful to pretend that you can. I suspect that epidemiologists, and others in the medical community, understand this because of their adherence to the Hippocratic oath. Primum non nocere: First, do no harm. Much of the most thoughtful work on the use and abuse of statistical models and the proper role of prediction comes from people in the medical profession.88 That is not to say there is nothing on the line when an economist makes a prediction, or a seismologist does. But because of medicine’s intimate connection with life and death, doctors tend to be appropriately cautious. In their field, stupid models kill people. It has a sobering effect. There is something more to be said, however, about Chip Macal’s idea of “modeling for insights.” The philosophy of this book is that prediction is as much a means as an end. Prediction serves a very central role in hypothesis testing, for instance, and therefore in all of science.89 As the statistician George E. P. Box wrote, “All models are wrong, but some models are useful.”90 What he meant by that is that all models are simplifications of the universe, as they must necessarily be. As another mathematician said, “The best model of a cat is a cat.”91 Everything else is leaving out some sort of detail. How pertinent that detail might be will depend on exactly what problem we’re trying to solve and on how precise an answer we require.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“This is an example of an out-of-sample problem. As easy as it might seem to avoid this sort of problem, the ratings agencies made just this mistake. Moody’s estimated the extent to which mortgage defaults were correlated with one another by building a model from past data—specifically, they looked at American housing data going back to about the 1980s.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“An admonition like "The more complex you make the model, the worse the forecast gets." is equivalent to saying "Never add too much salt to the recipe." How much complexity-how much salt-did you begin with? If you want to get good at forecasting, you'll need to immerse yourself in the craft and trust your own taste buds.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—But Some Don't

“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.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

“You will need to learn how to express-and quantify-the uncertainty in your predictions. You will need to update your forecast as facts and circumstances change. You will need to recognize the wisdom in seeing the world from a different viewpoint. The more you are willing to do these things, the more capable you will be of evaluating a wide variety of information without abusing it.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—But Some Don't