The Ten Equations That Rule the World: And How You Can Use Them Too

The Ten Equations That Rule the World: And How You Can Use Them Too

by David Sumpter

David Sumpter is Professor of Applied Mathematics at the University of Uppsala, Sweden, and the author of Soccermatics and Outnumbered. His scientific research ranges from ecology and biology to political science and sociology, and he has been an international consultant in government, artificial intelligence, sports, gambling, and finance.

1. Every problem can be broken down into three components: data, model, and nonsense.

Data is what you observe—it is your social media feed, your friends’ behavior, the things your colleagues at work do and say. Data doesn’t have to be numbers, and it can be subjective, but it has to come from what you see, hear, and read about in the world.

A model is how we reason about the data. How can we decide whether or not a person who makes a nasty comment is an idiot, or just a nice person having a bad day? How can we know if a four star-rated hotel is worth booking? How can we see our own successes and failures more clearly in relation to others’? Answering these questions starts by first thinking about whether we have the correct model—the correct way of seeing—the world. This is where equations come in, which help us improve our models of the world. They help us see why even nice people sometimes do bad things. They help us lift the filter that social media creates when we view the world. Models, when combined with data, bring clarity.

Then there is nonsense. We should read the word literally: “non-sense.” These are thoughts that are neither data (they don’t come from our senses) nor models (they do not help us reason about the data). We all have nonsense thoughts—when we daydream, when we listen to our favorite song, when we think about those around us. We don’t want to lose that nonsense, but we do want to understand it for what it is.

“We don’t want to lose that nonsense, but we do want to understand it for what it is.”

2. The numbers are in: We should be more forgiving.

Imagine a situation where someone has let you down or treated you badly. You want to work out whether they are an idiot who does nasty things because they enjoy it, or a nice person who has simply made a mistake. Start by thinking of the proportion of idiots and nice people in the world. (This is your model.) Let’s say you think that 95% of people are nice, so only 5% are idiots. And let’s also say that idiots do nasty things 50% of the time, and that even nice people make mistakes 10% of the time.

Now comes the data. Someone you have just met has let you down. Maybe they said something behind your back, or seemed to deliberately ignore you. The data is the person’s actions. The judgement equation—which originated more than 250 years ago from the work of an English reverend named Bayes—allows you to work out which model, the “idiot” model or the “nice” model, is correct.

It works like this: If there are 95 people (95% of 100) who are nice, then since 10% of these can make a mistake, then we might expect 9.5 of them to let you down. Of the 5% who are nasty, we expect 50%, or 2.5, to be deliberately nasty. Comparing 9.5 to 2.5 lets you see that, even after someone lets you down, the probability they are an idiot is only 2.5 divided by 12 (9.5 + 2.5). So, there’s only about a 20% chance that they are truly an idiot.

The numbers we use here are subjective, but the reasoning isn’t. Whatever your outlook, math says that you should almost always forgive others (the first few times at least). You can apply the same logic to worrying (or not) about an airplane crash, and even thinking about if your teenage kids are likely to become depressed from using their phones too much (the science says they are going to be fine). In short, the judgement equation, the rule that Bayes invented, usually tells us to give each other another chance…


F. Kaskais Web Guru

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