Coaching practices for Prior Probability Decision
Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For Prior Probability Decision, these are the strongest matches in the current practice library.
Does this sound like the set of challenges you might be facing?
- I want to know whether the evidence actually changed my mind or just confirmed where I already landed
- I keep playing out this decision in my head as if there’s just one way it goes
- One story has completely sold me on something and I’m about to act on it
- One compelling story or one impressive candidate completely swings my whole read, and afterward I can’t tell whether real new facts moved me or I just got swept up in how vivid and memorable that one case was.
- This is a one-way door
Practices that may help
- State your prior probability before seeing the evidence
Before looking at any data, commit to a numerical estimate of how likely something is.
Bayesian Thinking: How to Update Beliefs Rationally - 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 - Ask the base rate before evaluating the specific case
Before judging any individual instance, first establish how often this kind of thing happens in general.
Base-Rate Neglect: Why We Ignore the Odds - State your estimate before encountering vivid case information
Lock in a prior probability estimate before reading a compelling story or meeting a specific candidate.
Attribute Substitution: When Your Brain Answers a Different Question - 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 - Run a premortem before committing
Imagine the decision has already failed — then ask why.
Thinking in Bets - Recognition-Primed Decision Making
Gary Klein’s research found that experienced practitioners in high-stakes environments rarely compare options side by side. Instead, they recognize a situation as a familiar type, mentally simulate one course of action, and go with it if the simulation holds up — a process that is fast, accurate under time pressure, and breaks down predictably when the situation is genuinely novel. - Set default rules for willpower-intense situations
A pre-decided rule requires no willpower at the decision point — the decision has already been made.
Simple Heuristics: Gerd Gigerenzer’s Case for Fast and Frugal Thinking - Slow down on one-way doors
For irreversible decisions, invest in deliberation proportional to the downside — not to your confidence.
The Two-Way Door - Update beliefs by degrees, not wholesale
Treat new information as evidence that shifts probabilities, not as proof that changes everything.
Base-Rate Neglect: Why We Ignore the Odds
Related concerns
- High Stakes Uncertainty Decision
Choose the option whose worst plausible outcome is most survivable — when you can’t compute expected value, optimize the floor.
Use maximin reasoning for high-stakes, irreversible decisions under ambiguity
- Prior Probability
Before looking at any data, commit to a numerical estimate of how likely something is.
State your prior probability before seeing the evidence
- Prior Probability Bias
Before looking at any data, commit to a numerical estimate of how likely something is.
- Base Rate First Reasoning
Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information.
- Base Rate Question
Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information.
- Deliberate Decision Making
Sort decisions into low-stakes/high-stakes and reversible/irreversible before deciding.
Classify decisions by reversibility and stakes
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