  This presentation describes the Bayesian Block algorithm in the context of
its application to analysis of time series data from the Fermi Gamma Ray Space
Telescope. More generally this algorithm performs optimal segmentation analysis
on sequential data in any mode, with arbitrary sampling and in the presence of
gaps and exposure variations. A new procedure for correcting for backgrounds is
also described.
