&quot;Statistical Rethinking&quot; by Richard McElreath is really nice, light on maths but heavy on insights. He uses the book in a course and there are recordings of the lectures available on youtube.<p><a href="http:&#x2F;&#x2F;xcelab.net&#x2F;rm&#x2F;statistical-rethinking&#x2F;" rel="nofollow">http:&#x2F;&#x2F;xcelab.net&#x2F;rm&#x2F;statistical-rethinking&#x2F;</a><p>Edit: neither this book nor Kruschke&#x27;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 (<a href="http:&#x2F;&#x2F;www.eurasip.org&#x2F;Seminars&#x2F;Tutorials&#x2F;EUSIPCO2014%20Tutorial%20Bayesian%20Filtering%20and%20Smoothing.pdf" rel="nofollow">http:&#x2F;&#x2F;www.eurasip.org&#x2F;Seminars&#x2F;Tutorials&#x2F;EUSIPCO2014%20Tuto...</a>). You might want to read some introductory text on time series covering state space models first.<p>Edit again: The full text of &quot;Bayesian Filtering and Smoothing&quot; by Simo Sarkka is available online: <a href="http:&#x2F;&#x2F;users.aalto.fi&#x2F;~ssarkka&#x2F;pub&#x2F;cup_book_online_20131111.pdf" rel="nofollow">http:&#x2F;&#x2F;users.aalto.fi&#x2F;~ssarkka&#x2F;pub&#x2F;cup_book_online_20131111....</a>