Coaching practices for Base Rate Decisions
Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For Base Rate Decisions, these are the strongest matches in the current practice library.
Does this sound like the set of challenges you might be facing?
- One story has completely sold me on something and I’m about to act on it
- I build my estimate from my own optimistic story first and only glance at how long these things usually take at the very end as a sanity check
- When I look for examples of people who did what I’m about to do, all I find are the success stories
- I’m about to make a real decision based on a gut sense that this kind of thing happens "all the time," and I’ve just realized I have no idea how often it actually happens
- One thing happened that fits what I suspected and now I’m treating it as settled
Practices that may help
- Base-Rate Neglect: Why We Ignore the Odds
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. - 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 - Anchor on the base rate before adding inside-view details
Start your forecast from the class median, then adjust — do not start from your narrative and adjust to the base rate.
Reference Class Forecasting - Reference Class Forecasting
Reference class forecasting, developed by Daniel Kahneman and Amos Tversky and formalized by Bent Flyvbjerg, improves forecast accuracy by anchoring on the statistical distribution of outcomes for similar past projects rather than on the details of the current one. The method reliably corrects the optimism bias that inflates cost, time, and benefit estimates in planning — the evidence base here is real and specific. - Actively seek disconfirming cases
When researching base rates, specifically look for cases where things went badly — failure cases are underrepresented in natural memory.
The Outside View - Check the actual base rate before trusting your intuitive estimate
When an event feels common or rare, look up how often it actually happens.
The Availability Heuristic: Why Memorable Feels Probable - 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 - Always identify the denominator when evaluating risk or success
When a number or story is striking, ask: "Out of how many total cases?"
Base-Rate Neglect: Why We Ignore the Odds - Choose the right reference class for any prediction
Find the statistical base rate for the category your decision belongs to — not just the inspiring examples.
Survivorship Bias: Learning from What You Can’t See - Look up base rates before forming a resemblance judgment
Before deciding "this looks like X," ask how common X actually is in the relevant population.
The Representativeness Heuristic — Judging by Resemblance
Related concerns
- 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.
- Base Rate 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 Thinking
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.
- How To Use Base Rates In Decisions
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 Business
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 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.
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