👉 To calculate the probability of a sequence of events in a Bayesian context, we often use Bayes' Theorem. Given events A, B, and C, the probability of A given both B and C occurring (P(A|B,C)) is calculated using the formula: P(A|B,C) = [P(B|C,A)
P(C)] / P(B). Here, P(B|C,A) is the likelihood of event B given A has occurred, P(C|A,B) is the likelihood of event C given both A and B have occurred, and P(B) is the probability of event B occurring. The denominator P(B) normalizes the expression, ensuring the final result is a valid probability between 0 and 1. This formula allows us to update our belief about the occurrence of event A based on new evidence from both B and C, making it a powerful tool in statistical inference and machine learning.
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