This post is part of the 📖 Mental Models series.


Today, I am reading the 10th mental model What Would Bayes Do (WWBD)? from How to See More Clearly chapter of the book Mental Models written by Author Peter Hollins.

TL;DR! 💬

Mental Models are like giving a treasure map to someone lost in the woods. They provide instant understanding, context, and most importantly, a path to the end destination. Now imagine having such a map for all problems and decisions in your life.

In this book Mental Models, author Peter Hollins discuss 30 mental models that billionaires/CEOs, Olympic athletes, and scientists use to think differently and avoid mistakes.

Battle information overwhelm, focus on what really matters, and make complex decisions with speed and confidence.


Yesterday, I finished reading the 9th mental model Wait for the Regression to the Mean.

Chapter #2: How to See More Clearly

Mental Model #10:

What Would Bayes Do (WWBD)?

Use to calculate probabilities and predict the future based on real events.

Despite the fact that we stink at predicting the future, we try anyway.

Sometimes, when we crave a sense of assuredness about how future events will unfold, we rely on “experts”. But they’re usually wrong, regardless of what side of the thought spectrum they’re on.

Trying to understand what will happen in the near future becomes a game of salacious guessing rather than sincerely trying to forecast.

Although no proven model will provide a foolproof formula for predicting the future, there is a theorem that can at least provide some clarity about events in the world that may lead to a higher rate of successful prediction, a state of being better informed and able to handle reality.

This template is known as Bayes’ Theorem, named after the 18th-century mathematician Thomas Bayes.

There’s an actual formula to Bayes’ Theorem, and it’s helpful to know at least what the formula looks like:

Bayes' Formula

All you need is three numbers.

The probability of A occurring if B has already happened is written as P(A|B).

A is what you are solving for and what you are trying to predict.

The probability of B occurring if A has already happened is written as P(B|A).

The probability of A occurring on its own without B is written as P(A).

The probability of B occurring on its own without A is written as P(B).

The formula allows us to cut through the noise of what masquerades as impactful and ties it to something real and important.

The author provided an example in the book, but it is not ethical or feasible to produce in its entirety here. Please consider buying this great book and instantly upgrade your thinking process. By far, this is the best book I have read for years in this genre.


Key Takeaways

  • Bayes’ Theorem is something that does allow us to conclude the future: based on probabilities and taking into account events that have already occurred.

Summary

  • All you need are the rough probabilities of three elements to plug into the Bayes’ formula, and you will come to a more accurate conclusion than so-called experts. This is basic probabilistic thinking.

That’s it for today. Tomorrow, we will read the 10th mental model Do It Like Darwin, use to seek real, honest truth in a situation.

What mental models we've learned so far?
  1. Address “Important”; Ignore “Urgent”

    Identify and address important tasks, ignore urgent tasks. Delegate important but non-urgent task and delete not important and not urgent tasks.

  2. Visualize All the Dominoes

    Don’t stop your analysis once the most obvious situations are articulated. Consider as many long-term possible ramifications as you can. Think twice about what you’re doing, and it helps to eliminate rash decisions.

  3. Make Reversible Decisions

    If you want to make the best decision possible, you can go ahead and use reversible decisions to learn exactly what you need to know.

  4. Seek “Satisfaction

    We need far fewer things than we originally thought and that our desires are masquerading as needs. Use Seek “Satisfaction” to achieve your priorities and ignore what doesn’t matter by creating a default choice.

  5. Stay Within 40-70%

    Utilize this mental model by intentionally consuming less information and even overgeneralizing — this means not looking at the subtleties of your options.

  6. Minimize Regret

    Minimize Regret. Jeff Bezos developed what he calls the regret minimization framework. In it, he asks one to visualize themselves at age 80 and ask if they would regret making (or not making) a decision. This simplifies decisions by making them about one metric: regret.

  7. Ignore “Black Swans”

    A black swan event is an entirely unpredictable event that comes out of nowhere. Doing so skews all data and beliefs, and people start to take the black swan into account as a new normal. But these are just outliers that should be ignored.

  8. Look for Equilibrium Points

    This mental model is about noticing trends in progress.

    When you first start something, you go from zero to one—that’s an infinite rate of progress. Then you go from one to two, two to three, and so on, and the rate of progress slows, and the returns start diminishing.

    Somewhere around there is an equilibrium point that truly represents what the average mean will be. Don’t make the mistake of not waiting for it.

  9. Wait for the Regression to the Mean

    This mental model is the final mental model about seeing the whole picture in terms of information.

    A change without reason for the change is not a change; it’s just a deviation. As such, it doesn’t represent what will continue to happen in the future.

    A regression to the mean is when things settle back down and resume what they were doing before—this is representative of reality.

  10. What Would Bayes Do (WWBD)?

    Bayes’ Theorem is something that does allow us to conclude the future: based on probabilities and taking into account events that have already occurred. All you need are the rough probabilities of three elements to plug into the Bayes’ formula, and you will come to a more accurate conclusion than so-called experts. This is basic probabilistic thinking.

Mental Models: 30 Thinking Tools That Separate the Average from the Exceptional. Improved Decision-Making, Logical Analysis, and Problem-Solving

Author(s): Peter Hollins

Short Blurb: 30 Practical and applicable guidelines to think smarter, faster, and with expert insight (even if … Read more
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Part 10 of 29 in the 📖 Mental Models book series.

Series Start | Mental Models - Day 9 | Mental Models - Day 11



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