How to think like a Bayesian

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How to think like a Bayesian​

You’re often asked what you believe. Do you believe in God? Do you believe in global warming? Do you believe in life after love? And you’re often told that your beliefs are central to who you are, and what you should do: ‘Do what you believe is right.’

These belief-questions demand all-or-nothing answers. But much of life is more complicated than that. You might not believe in God, but also might not be willing to rule out the existence of a deity. That’s what agnosticism is for.

For many important questions, even three options aren’t enough. Right now, I’m trying to figure out what kinds of colleges my family will be able to afford for my children. My kids’ options will depend on lots of variables: what kinds of schools will they be able to get into? What kinds of schools might be a good fit for them? If we invest our money in various ways, what kinds of return will it earn over the next two, five, or 10 years?

Suppose someone tried to help me solve this problem by saying: ‘Look, it’s really simple. Just tell me, do you believe your oldest daughter will get into the local state school, or do you believe that she won’t?’ I wouldn’t know what to say to that question. I don’t believe that she will get into the school, but I also don’t believe that she won’t. I’m perhaps slightly more confident than 50-50 that she will, but nowhere near certain.

More:

How to think like a Bayesian | Psyche Guides

In a world of few absolutes, it pays to be able to think clearly about probabilities. These five ideas will get you started

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Fuzzy logic is a form of many-valued logic in which the truth value of variables may be any real number between 0 and 1. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false.[1] By contrast, in Boolean logic, the truth values of variables may only be the integer values 0 or 1.

The term fuzzy logic was introduced with the 1965 proposal of fuzzy set theory by mathematician Lotfi Zadeh.[2][3] Fuzzy logic had, however, been studied since the 1920s, as infinite-valued logic—notably by Łukasiewicz and Tarski.[4]

Fuzzy logic is based on the observation that people make decisions based on imprecise and non-numerical information. Fuzzy models or fuzzy sets are mathematical means of representing vagueness and imprecise information (hence the term fuzzy). These models have the capability of recognising, representing, manipulating, interpreting, and using data and information that are vague and lack certainty.[5][6]

Fuzzy logic has been applied to many fields, from control theory to artificial intelligence.
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Fuzzy logic - Wikipedia

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