I work with time series data every day in the domain of commercial real estate. One of my constant struggles is to extract an underlying long-term trend from the real estate cycle. I would love to try this here.
Can anyone suggest some Bayesian learning resources for a non-statistician?
http://xcelab.net/rm/statistical-rethinking/
Edit: neither this book nor Kruschke's are going to help you with time series in particular. Bayesian time series methods are based on state space models and are relatively complex (http://www.eurasip.org/Seminars/Tutorials/EUSIPCO2014%20Tuto...). You might want to read some introductory text on time series covering state space models first.
Edit again: The full text of "Bayesian Filtering and Smoothing" by Simo Sarkka is available online: http://users.aalto.fi/~ssarkka/pub/cup_book_online_20131111....
It gives a gentle but through introduction from first principles; lots of good intuition and 'why'.
It works well with "Probabilistic Programming & Bayesian Methods for Hackers" also mentioned, but I'd start with this. It is much more accessible than many other introductory books, IMO.