Category Archives: Bayesian Paradigm

What is a Bayesian Network ?

Bayesian network

A Bayesian network is a type of probabilistic graphical model, which can simultaneously represent a multitude of relationships between variables in a system.

The graph of a Bayesian network contains nodes (representing variables) and directed arcs that link the nodes. The arcs represent the relationships of the nodes.


Whereas traditional statistical models are of the form y=f(x), Bayesian networks do not have to distinguish between independent and dependent variables. Rather, a Bayesian network approximates the entire joint probability distribution of the system under study.

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Bayesian Networks from a Public Health Practitioner’s Perspective

 A bayesian network can be viewed

  • as a practically feasible form of knowledge representation
  •  attractive for exploring and explaining complex problems

Typically, a multi-level hierarchical structure could be characterized , in the present case with four levels,

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About Bayesian statistics

Over the last 25 years, Bayesian networks have emerged as a practically feasible form of knowledge representation. With the ever-increasing computing power, Bayesian networks are now a powerful tool enabling deep understanding of complex, multi-dimensional problem domains (Lynch., 2007). Their computational efficiency and inherently visual structure make Bayesian networks attractive for exploring and explaining complex problems.

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