This course is a follow-up of the data analysis course PHY231. The course is worth 2 ECTS and is focussed on some more practical aspects of data analysis. The course will be split into two parts. The first half will be a set of three lectures with accompanying exercise sheets. The second half will be a three-week data analysis project with a report and presentations due in May. The schedule is shown below:
Time and location: Y36 K 08 on Tuesdays at 10:15-12:00
Zoom link for lectures: [here] Password communicated by email (please ask if you are not yet subscribed).
|22nd Feb||Lecture1 - Monte Carlo techniques (PDF, 23 MB)|
|1st Mar||Exercise session - sheet01 (PDF, 193 KB) gauss_data (TXT, 2 KB)|
|15th Mar||Exercise session sheet02 (PDF, 128 KB) signal_and_background.txt (TXT, 16 KB)|
|22nd Mar||Lecture3 - Multivariate classification (PDF, 2 MB)|
|29th Mar||Exercise session sheet03 (PDF, 112 KB) selection_skeleton.py (PY, 3 KB) signal.txt (TXT, 1 MB) background.txt (TXT, 1 MB)|
ProjectI (PDF, 1 MB) (Tracking Detector)
ProjectII (PDF, 158 KB) (Compton Scattering)
ProjectIII (PDF, 174 KB) (Experiment design)
ProjectIV (PDF, 212 KB) (Pion decay)
|12th Apr||Status updates|
|10th May||Project reports due|
|17th May||Project presentations|
The course will be graded 1-6 with 50% of the grade coming from the exercise sheets and 50% coming from the project (report+presentations). A requirement to pass the course will be 50% of the marks from the exercise sheets and 50% on the project.