Please help, thank you

Consider the following graphs with 4 vertices: G1 = {(1, 2); (1, 4); (2,3)} G2 = {(1, 3); (2, 3); (3, 4); (1, 4); (2,4)} G3 = {(2, 4), (2,3)} G4 = {(1, 2); (3, 4); (2, 3); (2, 4) } G5 = {(2, 3); (2, 4); (3, 4) }. The above notation means: if a pair (i, j) is present in the graph then there is an edge between i and j. We adopt a Bayesian approach and we assume that the data follows a 4- dimensional Gaussian distribution. Infer the graph structure (and motivate your answer) when the posterior probabilities for the graphs are: 1. "(Gi|data) = 0.2, T(G2|data) = 0.5, "(G3|data) = 0.1, "(G4|data) = 0.1 and T(Gs data) = 0.1. [10 marks] 2. T(Gi data) = 0.08, T(G2|data) = 0.23, T(G3|data) = 0.23, T (G4|data) = 0.23 and T (Gs|data) = 0.23. [10 marks] 3. T(G1 data) = 0.3, T(G2)data) = 0.08, "(G3|data) = 0.3, T(G4|data) = 0.02 and 7(Gs|data) = 0.3. [10 marks]