# How to calculate the Probability for the Unconditional Node in the Bayesian Belief Network?

In the popular example for Bayesian Belief network Burglary Alarm how is the probability for burglary P(B) and earthquake P(E) calculated as 0.001 and 0.002 respectively?

Is it an assumption made or there is some calculation involved ? I can understand the conditional probabilities for the child nodes but not sure how the probability for the nodes Burglary and Earthquake are getting calculated?

• Just looking at the slide deck. I think they are Priors (just known a priori). Assumptions, if you will. Just my 2 cents. – knb Mar 29 '18 at 10:46