Speaker
Description
The lecture will address the topic of combining information
from different sources in an analysis of Particle Physics data.
The general formalism by which this is done in both the
Bayesian and Frequentist approaches will first be reviewed.
Combination of results relies fundamentally on constructing
a likelihood that reflects all of the available data. Often this
requires some approximations and assumptions as the
detailed information needed to write down the full likelihood
may not be available. An important aspect of combined (and
individual) data analyses is the assignment of uncertainties to estimates
to nuisance parameters. A method will be described by which
uncertainties on the assigned uncertainties
themselves can be incorporated, and the impact of this type of
a model on combinations will be shown.
Link to the python code used for the example of a+bx fit:
https://www.pp.rhul.ac.uk/~cowan/stat/fitCombo.py
https://www.pp.rhul.ac.uk/~cowan/stat/fitCombo.ipynb
