The Signal and the Noise
The Signal and the Noise
Why Most Predictions Fail but Some Don’t By Nate Silver
Most of us aren’t very good at making accurate predictions, and the consequences - like backing the wrong initiative at work or picking the wrong stock for our portfolio - can be painful. The most accurate forecasters tend to have a superior ability to identify a true signal – a reliable indicator that something important is about to happen – from a false one. In other words, they separate the “signal” from the “noise”. The most common prediction failures are the result of: 1. 2. 3. 4.
Focusing on signals that tell a story about the world as we’d like it to be, not how it is; Ignoring risks that are hard to measure, even when they pose the greatest threats; Making assumptions about the world that are much cruder than we realize; and Hating uncertainty, even when it’s an irreducible part of the problem we’re trying to solve.
The concepts of risk and uncertainty can be tricky ones to grasp. Risk, is something that you can quantify. Uncertainty, on the other hand, is risk that is hard, or impossible, to measure. So, if uncertainty is all around us, and if it defies measurement, how can we account for the problem of uncertainty in our predictions? By applying the following three principles:
Principle 1: Think Probabilistically Don’t think in absolute terms. There’s always a range of possible outcomes, so assign a probability to each one. This keeps you aware that even highly unlikely things can happen.
Principle 2: Today’s Forecast Is the First Forecast of the Rest of Your Life The world is a dynamic place. Don’t be afraid to change your predictions when new information comes to light. Make the best forecast possible today – regardless of what you said before. If you have reason to think that yesterday’s forecast was wrong, there is no glory in sticking to it.
Principle 3: Look for Consensus The expert consensus can be wrong. But historical evidence suggests that aggregate or group forecasts are typically 15 to 20 percent more accurate than individual ones.
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Why Most Predictions Fail but Some Don’t By Nate Silver
Most of us aren’t very good at making accurate predictions, and the consequences - like backing the wrong initiative at work or picking the wrong stock for our portfolio - can be painful. The most accurate forecasters tend to have a superior ability to identify a true signal – a reliable indicator that something important is about to happen – from a false one. In other words, they separate the “signal” from the “noise”. The most common prediction failures are the result of: 1. 2. 3. 4.
Focusing on signals that tell a story about the world as we’d like it to be, not how it is; Ignoring risks that are hard to measure, even when they pose the greatest threats; Making assumptions about the world that are much cruder than we realize; and Hating uncertainty, even when it’s an irreducible part of the problem we’re trying to solve.
The concepts of risk and uncertainty can be tricky ones to grasp. Risk, is something that you can quantify. Uncertainty, on the other hand, is risk that is hard, or impossible, to measure. So, if uncertainty is all around us, and if it defies measurement, how can we account for the problem of uncertainty in our predictions? By applying the following three principles:
Principle 1: Think Probabilistically Don’t think in absolute terms. There’s always a range of possible outcomes, so assign a probability to each one. This keeps you aware that even highly unlikely things can happen.
Principle 2: Today’s Forecast Is the First Forecast of the Rest of Your Life The world is a dynamic place. Don’t be afraid to change your predictions when new information comes to light. Make the best forecast possible today – regardless of what you said before. If you have reason to think that yesterday’s forecast was wrong, there is no glory in sticking to it.
Principle 3: Look for Consensus The expert consensus can be wrong. But historical evidence suggests that aggregate or group forecasts are typically 15 to 20 percent more accurate than individual ones.
TheBusinessSource.com
All Rights Reserved
