Applied Statistics - Week 5
The following is a description of what we will go through during this
week of the course. The chapter references and computer exercises are
considered read, understood, and solved by the beginning of the
following class, where I'll shortly go through the exercise
solution.
General notes, links, and comments:
:
Monday:
We will spend both Monday and Tuesday on a larger exercise, which
illustrates the idea of separating data into catagories, and how to
measure and optimise the performance of this.
The data is from
ATLAS
testbeam data at CERN and deals with separating
particles in a beam into electrons and pions, but could in principle
be from any other area of research and/or business.
The subject also brings us to one of the last (formal) lectures,
which is on
Bayes' Theorem. Many of you know this theorem
already, but I'll try to bring a general perspective on data analysis
along with it.
Reading:
Barlow, chapter 7.
Lecture(s):
Bayes' Theorem
Computer Exercise(s):
Analysis
of ATLAS testbeam data:
ATLAStestbeam.py
and data.
Tuesday:
We will continue with the ATLAS testbeam exercise, and I will ask you
to submit some key numbers that you should have obtained from the
analysis. In addition we will go through project 1, and finally I'll
arrange for a Questions-and-Answers session on the problem set towards
the end of class.
Reading:
You should by now have read curriculum (roughly Barlow chapters 1-8).
Lecture(s):
There are no more formal lectures.
Computer Exercise(s):
Analysis
of ATLAS testbeam data:
ATLAStestbeam.py
and data.
As a courtesy, here is code doing a ROC curve calculation:
CalculateROCexample.py.
Friday:
The last day of class in the year, we will dedicate to getting
project 2 started
for all groups. By the end of the day, you should have:
Data ready on your computer.
Hypotheses that you want to test.
A clear mind on what your project is about.
Reading:
You should by now have read curriculum (roughly Barlow chapters 1-8).
Lecture(s):
There are no more formal lectures.
Computer Exercise(s):
Your project defines the exercise!
Last updated: 12th of December 2015.