Final answer:
The associated independence assertion is: B) False.
Step-by-step explanation:
In graphical models, the assertion of independence or conditional independence is based on the presence or absence of direct connections between variables. If two variables are connected in the graphical model, the assertion of independence between them would be false. This implies that the variables are not independent given the information of their connected neighbors in the graph.
For instance, in a Bayesian network where variables are represented as nodes and edges depict relationships, if there's a direct edge between two nodes, say A and B, the assertion of independence between A and B given their connected neighbors in the graph would be false. The presence of an edge implies some form of dependence or conditional dependence between these variables, as the edge represents a direct influence or relationship.
Hence, the assertion of independence would be false when direct connections exist between variables in the graphical model.
Correct answer: B) False