? ? a. If the A-E (random variable) are independent of each other, write the joint probability

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a. If the A-E (random variable) are independent of each other, write the joint probability distribution equation of the network! b. If the A-E (random variable) is connected as in network 1, write the joint probability distribution equation of the network! c. If the A-E (random variable) is connected as in network 2, write the joint probability distribution equation of the network! d. If given every random variable (AE) has 2 possible values (for example: A → + a or-a) and is connected as in network 2, then if given information that P (+a)= 0.6, P (+ b | -a) = 0.1, P (+ b + a) = 0.9, P (+ c | -a) = 0.8, P (+ c + a) = 0.5, P (+ d | -a, -b) = 0.1, P (+ d + a, -b) = 0.9, P (+ d |-a, + b) = 0.3, P (+ d | + a, + b) = 0.95, P (+ e -d) = 0.8, and P (+ e + d) = 0.1; write down the CPT of each node. e. Still with the information given in point (d), count P (+ a, + b + c, + d, + e)! f. Still with the information given in point (d), count P (+ e + a)! Bayesian Network C A E B Network 1 D B A D Network 2 C E a. If the A-E (random variable) are independent of each other, write the joint probability distribution equation of the network! b. If the A-E (random variable) is connected as in network 1, write the joint probability distribution equation of the network! c. If the A-E (random variable) is connected as in network 2, write the joint probability distribution equation of the network! d. If given every random variable (AE) has 2 possible values (for example: A → + a or-a) and is connected as in network 2, then if given information that P (+a)= 0.6, P (+ b | -a) = 0.1, P (+ b + a) = 0.9, P (+ c | -a) = 0.8, P (+ c + a) = 0.5, P (+ d | -a, -b) = 0.1, P (+ d + a, -b) = 0.9, P (+ d |-a, + b) = 0.3, P (+ d | + a, + b) = 0.95, P (+ e -d) = 0.8, and P (+ e + d) = 0.1; write down the CPT of each node. e. Still with the information given in point (d), count P (+ a, + b + c, + d, + e)! f. Still with the information given in point (d), count P (+ e + a)! Bayesian Network C A E B Network 1 D B A D Network 2 C E