Coaching practices for How to Think in Probabilities
Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For How to Think in Probabilities, these are the strongest matches in the current practice library.
Does this sound like the set of challenges you might be facing?
- I keep playing out this decision in my head as if there’s just one way it goes
- I talk about the future in flat will-or-won’t terms
- I throw around words like “probably” and “pretty likely” and they mean nothing
- I make these probability guesses in my head
- I slap a confident-sounding percentage on things I genuinely have no basis to estimate, just to seem rational
Practices that may help
- Enumerate scenarios and their probabilities before deciding
Write down each meaningful outcome, assign a probability, and compute the weighted total.
Expected Value Thinking: Deciding Under Uncertainty - Think in probabilities, not certainties
Replace "I think this will happen" with "I think there is a 70% chance this will happen."
Thinking in Bets - Think and communicate in explicit probabilities
Replace vague language ("probably," "likely") with numerical probabilities.
Superforecasting - Keep a decision journal to score your EV estimates
Log your probability estimates and payoff predictions, then compare them to what happened.
Expected Value Thinking: Deciding Under Uncertainty - Distinguish uncertainty (quantifiable) from ignorance (unquantifiable)
Know when you can assign a probability and when the situation is so novel that a number would be fabricated.
Calibration Training - Bayesian Thinking: How to Update Beliefs Rationally
Bayesian thinking is the practice of holding beliefs as probabilities and updating them systematically when new evidence arrives — rather than treating beliefs as simply true or false. The mathematical framework is well established; the challenge is building the habits of explicit probability estimation and honest belief updating that make it practical. - Expected Value Thinking: Deciding Under Uncertainty
Expected value thinking multiplies each possible outcome by its probability and sums the results, giving a single number that represents the average payoff of a decision. It is the mathematical foundation of rational decision-making under uncertainty — well grounded in decision theory — but it has real limits: probabilities are often uncertain, outcomes are not always quantifiable, and raw expected value ignores risk aversion that can be legitimate. - Use reference classes to ground personal estimates in base rates
Before estimating how your situation will unfold, find similar past situations and check what happened.
Bayesian Thinking: How to Update Beliefs Rationally - Use maximin reasoning for high-stakes, irreversible decisions under ambiguity
Choose the option whose worst plausible outcome is most survivable — when you can’t compute expected value, optimize the floor.
Ambiguity Aversion — Why Unknown Odds Feel Worse Than Bad Odds - Practice probabilistic calibration by tracking your predictions
Assign explicit probability estimates to your predictions and track whether they come true at the right rate.
Base-Rate Neglect: Why We Ignore the Odds
Related concerns
- How To Think Probabilistically
Write down each meaningful outcome, assign a probability, and compute the weighted total.
Enumerate scenarios and their probabilities before deciding
- How To Avoid Probability Mistakes
Assign explicit probability estimates to your predictions and track whether they come true at the right rate.
Practice probabilistic calibration by tracking your predictions
- Probabilistic Thinking Practice
Bayesian thinking is the practice of holding beliefs as probabilities and updating them systematically when new evidence arrives — rather than treating beliefs as simply true or false. The mathematical framework is well established; the challenge is building the habits of explicit probability estimation and honest belief updating that make it practical.
- Expected Value Thinking Deciding Under Uncertainty With My Partner
Expected value thinking multiplies each possible outcome by its probability and sums the results, giving a single number that represents the average payoff of a decision. It is the mathematical foundation of rational decision-making under uncertainty — well grounded in decision theory — but it has real limits: probabilities are often uncertain, outcomes are not always quantifiable, and raw expected value ignores risk aversion that can be legitimate.
- Probabilistic Thinking
Bayesian thinking is the practice of holding beliefs as probabilities and updating them systematically when new evidence arrives — rather than treating beliefs as simply true or false. The mathematical framework is well established; the challenge is building the habits of explicit probability estimation and honest belief updating that make it practical.
- Probability Weighted Decision Making
Write down each meaningful outcome, assign a probability, and compute the weighted total.
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