Page 2 of this book says
The joint probability distribution is central to probabilistic inference, because once we know the joint distribution we can answer every possible probabilistic question that can be asked about these variables. We can calculate conditional or joint probabilities over any subset of the variables, given their joint distribution. This is accomplished by operating on the probabilities for the relevant rows in the table.
What does central mean here?