I've solved this. Thanks anyway.
I am struggling to calculate the ratios for converging connections in bayesian networks.
For example...
TBoC ---> D <--- B
This is modelled by the formula, p(D | TBoC, B).
When the TBoc and D are instantiated... p(D = yes | TBoC = yes | B),
The likelihood ratio is 90:70.
and the Priors of B are true: 45% and false: 55%.
I know the answers I am looking for are 51.266% and 43.734%, but I just can't seem to work out how to do this!
How do I work out the change in chances of the patient having Bronchitis?
Looking forward to any help,
Thanks.