Content delivery and attendance
The situation can rapidly change so please keep up to date with the latest information. The following was up-to-date on 17th September.
Due to the pandemic, the course delivery will be different this year compared to last time.
Lectures: It is planned to have students on site for live lectures. The lectures will also be simultaneously broadcast via Zoom* for those who cannot or do not wish to attend in person.
Exercises: There are two rooms available for exercise classes in python. The places will be decided on a first-come-first-serve basis but there should be enough space for everyone.
Time: This is a recurring meeting Meet anytime https://uzh.zoom.us/j/95525151670
Meeting ID: 955 2515 1670
Passcode: Communicated via email
The course will be graded 1-6. With 50% of the grade from exercise sheets and another 50% from a test given in the middle of the course. The requirements to pass the course will be to get at least 50% of the marks from the exercise sheets and at least 50% of the marks in the exam.
Midterm test (16th November at 15:00 in Y36 J 23 and Y36 J 33):
* The midterm test is worth 50% of the overall grade
* It is based on the first eight lectures.
* There will be a formula sheet which will be shared beforehand this formula sheet is provided as part of the exam.
* Apart from the formula sheet, the test is closed book.
* A calculator is allowed to be used during the exam (but likely not needed).
* The midterm test will be in person with a COVID certificate required for presence.
Vadym Denysenko / Jonas Eschle / Yuta Takahashi
|Lectures:||Tuesdays 09:00 to 09:45 in Y16 G 05|
|Exercises:||Tuesdays 15:00 to 17:00 in Y36 J 23 und Y36 J 33|
Information and material
Material from previous and related courses
- Data analysis (HS2020; P. Owen) - Lectures from last year
- Datenanalyse (HS2018; O. Steinkamp) - Lectures from 2018 (slightly different content).
- Datenanalyse (SS2004; H.Pruys) - Lectures from 2004, which have some things in common.
- Statistical Methods and Analysis Techniques in Experimental Physics, (FS2015; C.Grab) - Further lectures within the joint masters program "Particle Physics" between UZH and ETH