- #1
xeon123
- 90
- 0
in the Bayes' theorem, why P(B|A)*P(A) is divided by P(B)? What we want no achieve with the fraction?
Bayes' Theorem is a mathematical formula that helps calculate the probability of an event occurring based on prior knowledge or information. It is used to update the probability of an event as new information becomes available.
The key components of Bayes' Theorem are the prior probability (P(A)), the likelihood (P(B|A)), and the total probability (P(B)). These are used to calculate the posterior probability (P(A|B)), which is the updated probability after incorporating new information.
Bayes' Theorem is widely used in fields such as medical diagnosis, spam filtering, and financial forecasting. For example, in medical diagnosis, it can help determine the likelihood of a patient having a certain disease based on their symptoms and other factors.
One limitation of Bayes' Theorem is that it assumes that the prior probability and the likelihood are independent of each other. This may not always be the case in real-life scenarios. It also requires accurate and unbiased data to produce reliable results.
Bayes' Theorem helps to update the probability of an event as new information becomes available, making it a more accurate representation of the real-world probability. It also allows for the incorporation of prior knowledge and can handle complex scenarios with multiple variables and outcomes, resulting in more accurate probabilities.