The Signal and the Noise Quotes

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The Signal and the Noise: Why So Many Predictions Fail - But Some Don't The Signal and the Noise: Why So Many Predictions Fail - But Some Don't by Nate Silver
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The Signal and the Noise Quotes (showing 1-30 of 75)
“Most of you will have heard the maxim "correlation does not imply causation." Just because two variables have a statistical relationship with each other does not mean that one is responsible for the other. For instance, ice cream sales and forest fires are correlated because both occur more often in the summer heat. But there is no causation; you don't light a patch of the Montana brush on fire when you buy a pint of Haagan-Dazs.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“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.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“If political scientists couldn’t predict the downfall of the Soviet Union—perhaps the most important event in the latter half of the twentieth century—then what exactly were they good for?”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“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.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“Good innovators typically think very big and they think very small. New ideas are sometimes found in the most granular details of a problem where few others bother to look. And they are sometimes found when you are doing your most abstract and philosophical thinking, considering why the world is the way that it is and whether there might be an alternative to the dominant paradigm. Rarely can they be found in the temperate latitudes between they two spaces, where we spend 99 percent of our lives.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“Shakespeare's plays often turn on the idea of fate, as much drama does. What makes them so tragic is the gap between what his characters might like to accomplish and what fate provides them.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“The signal is the truth. The noise is what distracts us from the truth.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“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.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“The more interviews that an expert had done with the press, Tetlock found, the worse his predictions tended to be.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“The story the data tells us is often the one we’d like to hear, and we usually make sure that it has a happy ending.”
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
“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
“Risk, as first articulated by the economist Frank H. Knight in 1921,45 is something that you can put a price on. Say that you’ll win a poker hand unless your opponent draws to an inside straight: the chances of that happening are exactly 1 chance in 11.46 This is risk. It is not pleasant when you take a “bad beat” in poker, but at least you know the odds of it and can account for it ahead of time. In the long run, you’ll make a profit from your opponents making desperate draws with insufficient odds. Uncertainty, on the other hand, is risk that is hard to measure. You might have some vague awareness of the demons lurking out there. You might even be acutely concerned about them. But you have no real idea how many of them there are or when they might strike. Your back-of-the-envelope estimate might be off by a factor of 100 or by a factor of 1,000; there is no good way to know. This is uncertainty. Risk greases the wheels of a free-market economy; uncertainty grinds them to a halt.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“But forecasters often resist considering these out-of-sample problems. When we expand our sample to include events further apart from us in time and space, it often means that we will encounter cases in which the relationships we are studying did not hold up as well as we are accustomed to. The model will seem to be less powerful. It will look less impressive in a PowerPoint presentation (or a journal article or a blog post). We will be forced to acknowledge that we know less about the world than we thought we did. Our personal and professional incentives almost always discourage us from doing this.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“He does not depend on insider tips, crooked referees, or other sorts of hustles to make his bets. Nor does he have a “system” of any kind. He uses computer simulations, but does not rely upon them exclusively.”
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
“Economy is not baseball, where the game is always played by the same rules.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“When catastrophe strikes, we look for a signal in the noise - anything that might explain the chaos that we see all around us and bring order to the world again.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“Laplace’s Demon:”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“Men may construe things, after their fashion / Clean from the purpose of the things themselves.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“poker is a hard way to make an easy living.”
Nate Silver, The Signal and the Noise: The Art and Science of Prediction
“For Popper, a hypothesis was not scientific unless it was falsifiable—meaning that it could be tested in the real world by means of a prediction.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“Stories of prediction are often those of long-term progress but short-term regress”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't
“The most basic tenet of chaos theory is that a small change in initial conditions—a butterfly flapping its wings in Brazil—can produce a large and unexpected divergence in outcomes—a tornado in Texas.”
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 expand our sample to include events further apart from us in time and space, it often means that we will encounter cases in which the relationships we are studying did not hold up as well as we are accustomed to. The model will seem to be less powerful. It will look less impressive in a PowerPoint presentation (or a journal article or a blog post). We will be forced to acknowledge that we know less about the world than we thought we did. Our personal and professional incentives almost always discourage us from doing this. We forget—or we willfully ignore—that our models are simplifications of the world. We figure that if we make a mistake, it will be at the margin.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“When they play against each other, the game usually comes down to who can find his opponent’s blind spots first.”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“The fashionable term now is “Big Data.” IBM estimates that we are generating 2.5 quintillion bytes of data each day, more than 90 percent of which was created in the last two years.36”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't
“If you correctly detect an opponent’s bluff, but he gets a lucky card and wins the hand anyway, you should be pleased rather than angry, because you played the hand as well as you could. The irony is that by being less focused on your results, you may achieve better ones.”
Nate Silver, The Signal and the Noise: The Art and Science of Prediction
“Data Is Useless Without Context”
Nate Silver, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

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