I have a large amount of data, given totals for every hour over a year period for the following columns:
# of Jams
Jam event time in minutes
# of Full occurances
Full event time in minutes
and Runtime, product flow (counts)

I am trying to create a bayesian model using iPython and specifically, this project.
https://github.com/CamDavidsonPilon/...ds-for-Hackers

But, after reading through the project, and trying to think about what a bayesian belief network is, basing my analysis on prior probabilities seems very confusing to me.

I am open to any ideas for how I could show the effects of Jam and Full conditions have on the runtime or counts. Any suggestions would be helpful and I would really like to do something with python.