Base Rate Fallacy Examples in Psychology, Statistics & Heuristics
Base Rate Fallacy
What Is the Base Rate Fallacy?
The base rate fallacy is a statistical error that occurs when people draw conclusions about the probability of an event based on what they know about base rates. It is a cognitive bias where people make judgments based on the most common outcome.
Base Rate Fallacy is a statistical error that occurs when people use the base rate to make predictions about an individual. The tendency to believe that a statement is more likely than it really is because it’s been presented as being more probable.
For example, if you have two groups of people:
- Group A has 8 men and 3 women;
- Group B has 7 men and 7 women.
Then group B will be seen as more likely to contain a woman than group A even though this conclusion is not accurate because both groups are equally likely to contain a woman (3/11 for group A vs. 7/14 for group B).
This type of reasoning can also lead to overconfidence in predictive judgments or decisions from small samples with low base rates, such as predicting the sex of unborn babies after looking at ultrasound scans where there are only two possible outcomes (male or female). Still, the sample size is very small (e.g., 1-in-500).
The base rate fallacy is the tendency to ignore statistical data in favor of a more easily understood piece of information.
Base Rate Fallacy Examples
Base Rate Fallacy Real-Life Examples
Base Rate Fallacy in Real Life:
For example, if you’re at a casino and see that 90% of people are losing money, your chances of winning are 10%, but it’s 50% in reality.
Base Rate Fallacy Examples in Insurance & Business
Base Rate Fallacy is a statistical error that occurs when people use the base rate to make predictions about an individual.
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The base rate fallacy is often seen in insurance claims, where it’s more likely for someone with a high deductible to file a claim than someone with a lower deductible.
This happens because the person who files the claim will have their costs reimbursed by their insurer, while those without a claim won’t be reimbursed.
Example of Base Rate Fallacy in Heuristics
The base rate fallacy is a logical fallacy that occurs when someone evaluates the probability of an event by using the base rate instead of considering other relevant information.
For example, if you are told that 90% of people who have cancer will die from it and then asked to evaluate what percentage of people with cancer will die from it, most people would say “90%” because they are relying on the base rate.
However, this ignores other relevant information, such as how old these patients were or whether they smoked cigarettes
The base-rate fallacy is an example of how heuristics can lead to incorrect inferences about probabilities and risks
Base Rate Fallacy examples in Psychology
Examples of Base Rate Fallacy in Psychology:
Base Rate Fallacy is a type of logical fallacy that occurs when people focus on the probability of an event happening rather than how likely it is to happen.
For example, if you are told that 90% of all psychologists have a Ph.D. and you know someone who has a Ph.D. in psychology, then there’s only a 10% chance they don’t have one.
This can lead to incorrect conclusions because the person making the argument might not be aware that most doctors do not specialize in psychiatry.
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Another Example:
For example, if you are told that 90% of people who have had cancer will survive for at least 10 years after diagnosis, but then you hear about someone who has died from cancer, you might think that person’s death was caused by their cancer even though they would not be included in the statistics because they did not live long enough.
This type of error can lead to biased decisions and faulty conclusions.