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:
Contact time: Tuesdays at 10:00
Zoom link for lectures: [here] Password communicated by email (please ask if you are not yet subscribed).
Zoom link for exercises: [here]
|23rd Feb||Lecture1 - Monte Carlo techniques (PDF, 7 MB)|
|2nd Mar||Exercise session - sheet1 (PDF, 195 KB) gauss_MC (TXT, 2 KB)|
|16th Mar||Exercise session sheet2 (PDF, 120 KB)|
|23rd Mar||Lecture - Multivariate analysis (PDF, 2 MB)|
|30th Mar||Exercise session sheet3 (PDF, 112 KB) signal.txt (TXT, 1 MB)background.txt (TXT, 1 MB)skeleton.py (PY, 3 KB)|
Introduction to projects
|20th Apr||Progress reports|
|4rd May||Project reports due|
|11th 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.