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An example of the base rate fallacy is the false positive paradox (also known as accuracy paradox).This paradox describes situations where there are more false positive test results than true positives (this means the classifier has a low precision).
Naturalistic fallacy fallacy is a type of argument from fallacy. Straw man fallacy – refuting an argument different from the one actually under discussion, while not recognizing or acknowledging the distinction. [110] Texas sharpshooter fallacy – improperly asserting a cause to explain a cluster of data. [111]
For example, if the control group, using no treatment at all, had their own base rate of 1/20 recoveries within 1 day and a treatment had a 1/100 base rate of recovery within 1 day, we see that the treatment actively decreases the recovery. The base rate is an important concept in statistical inference, particularly in Bayesian statistics. [2]
A base rate is a phenomenon's basic rate of incidence. The base rate fallacy describes how people do not take the base rate of an event into account when solving probability problems. [12] This was explicitly tested by Dawes, Mirels, Gold and Donahue (1993) who had people judge both the base rate of people who had a particular personality trait ...
Base rate fallacy or base rate neglect, the tendency to ignore general information and focus on information only pertaining to the specific case, even when the general information is more important. [48] Compassion fade, the tendency to behave more compassionately towards a small number of identifiable victims than to a large number of ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.
In another example of near-total neglect of probability, Rottenstreich and Hsee (2001) found that the typical subject was willing to pay $10 to avoid a 99% chance of a painful electric shock, and $7 to avoid a 1% chance of the same shock. They suggest that probability is more likely to be neglected when the outcomes are emotion-arousing.
Several theories predict the fundamental attribution error, and thus both compete to explain it, and can be falsified if it does not occur. Some examples include: Just-world fallacy. The belief that people get what they deserve and deserve what they get, the concept of which was first theorized by Melvin J. Lerner in 1977. [11]