The purpose of this book is to provide a self-contained entry into practical
and computational Bayesian statistics using generic examples from the most
common models for a class duration of about seven blocks that roughly correspond to 13–15 weeks of teaching (with three hours of lectures per week), depending on the intended level and the prerequisites imposed on the students. (That estimate does not include practice—i.e., R programming labs, writing data reports—since those may have a variable duration, also depending on the st
udents’ involvement and their programming abilities.) The emphasis on practice is a strong commitment of this book in that its primary audience consists of graduate students who need to use (Bayesian) statistics as a tool to analyze their experiments and/or datasets.