# A “simple” explanation of the concept of D-separation in a Bayesian Network?

Hello everyone.

I'm looking for a "simple" explanation of the concept of D-separation in a Bayesian Network.

As far as I know the definition is "two variables (nodes) in the network are D-Separated if the information is "blocked" between the two nodes by some evidence about the nodes in the middle.

But I can't pratically understand the concept.

I don't have enough rep to use images so these are the links to the images (just 25kbyte each one) from my dropbox folder.

What I would like to understand if in these three patterns:

1. When there is NO evidence What (and why) nodes are D-separated from the each others
2. In what cases EVIDENCE about a specific node cause two nodes to be separated

Thank you in advance for any help.

Regards

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## 1 Answer

Try this tutorial http://www.andrew.cmu.edu/user/scheines/tutor/d-sep.html

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thank you. I'll take a look later and of cource if it solves my doubts I'll accept your answer –  Manuel Jun 20 '12 at 14:20