Using Netica develop the Bayesian network in Figure 3.2, and use that network to determine the following conditional probabilities:

1. P(F - y e s l S e x - male). Is this conditional probability different from P(F - yes)? Explain why it is or is not.
2. P(F - y e s l J - yes). Is this conditional probability different from P(F = yes)? Explain why it is or is not.
3. P(F - y e s l S e x - male, J - yes). Is this conditional probability different from P(F - y e s l J - yes)? Explain why it is or is not.
4. P(G - y e s l F - yes). Is this conditional probability different from P(G = yes)? Explain why it is or is not.
5. P(G - y e s l J - yes). Is this conditional probability different from P(G -
yes)? Explain why it is or is not.
6. P(G - y e s l J - yes, F - yes). Is this conditional probability different from P(G - y e s l F - yes)? Explain why it is or is not.
7. P(G - y e s l A - 8. P(G - y e s l A -

x Y N W Px=4 P=.8 P= .7/Pw=.2 T Figure 3.32: The noisy OR-gate model is assumed.