In order to understand Bayesian networks, individuals have collaborated together to create nodes about related concepts.

On March 14, 2020, S8 explained gave a general overview of belief propagation and gave a simple overview of its definition and connection to Bayesian networks. However, this general overview was likely not sufficient enough to fully understand the significance of this concept. 3 days after the initial proposal, on March 17, S4 then added more information on the details of the process, allowing for node to have more cohesive information. On the same day, S4 then made two more child nodes relating to this concept. With the addition of the new proposals, the presentation of belief propagation became more cohesive and better organized specific details pertaining to this topic.

An interesting point to note is that on the same day S8 created the node on belief propagation, they also created a child node that contained a picture showcasing with belief propagation, but did not include an explanation. However, almost 8 days later,  on March 22, S8 proposed an improvement to add a description explaining the steps in the image. Although not confirmed, it could be possible that S4's proposal on S8's node, prompted them to reassess their learning and presentation of the information and therefore want to improve their node to be more informative.

1Cademy Nodes for Bayesian Networks Analysis

- In the "Bayesian Networks" node one proposal helped improved the node by adding an image
- In "Bayes Theorem Overview," multiple people contributed various child nodes that relate to this topic
- For example, "Alternate Bayes' Theorem Equation" explores this topic in a different way
- Another individual helped explain one relevant example discussed in "The Book of Why" in the node "Inverse probability: break-cognitive asymmetry" which had a child node explained by another person, "Data could be reversed," which explains another example Pearl discusses in "The Book of Why"

University of Michigan - Ann Arbor

- "Author's reasons behind criticism of Bayesian Network"
- "Relation between Bayesian Networks and Causal Diagrams"
- "From objectivity to subjectivity"

Outside References
- "Helpful article about Bayesian Networks"
- "Reference for"How Bayesian Networks work""

Specific Nodes that were Helpful for Learning Bayesian Networks

- People have found outside references (like nodes "Helpful article about Bayesian Networks" and "Reference for How Bayesian Networks work") that could help clarify concepts that were discussed in "The Book of Why"

- Pearl goes into great detail about the development and usage of Bayesian networks. The structure of nodes allows easier access to previously discussed topics and concepts that were incorporated into this concept. In addition, it can be helpful to have nodes that summarize larger concepts, like "Relation between Bayesian Networks and Causal Diagrams" and "From objectivity to subjectivity."

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