Base Rate

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  • January 15, 2022
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Coursera

Topics: Probability, Bayes’ rule, Base Rate

Transcript Summary

Hypothetically, there is a disease called acalasia. It’s a terrible disease, and it can be fatal. But if you look at the symptoms, these are symptoms that almost anybody could have such as, slight weight loss, a little bit of a cough, etc. But it turns out that less than a million and six hundred thousand people suffer from this disease. So just because you have these symptoms, it does not mean that you’re likely to have this disease. This problem with the base fallacy in statistics is the confusion of two different conditional probabilities. The probability that you have this disease, given that you have these symptoms, is not the same as the probability that you have this symptom, given that you have this disease. The second probability is that you have the symptoms, which are very high if you have the disease. In a statistics class, Bayes’ Law determines how these probabilities are related to each other, and what determines how close these two things are, is what we call the base. In this equation, there are two probabilities, A and the probability of B. In other words, it’s the probability of a person having the disease overall in the population, and the probability of a person having those symptoms overall in the population.

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