Statistical Tools in Astrophysics (ASTM29/NAAS003)
Welcome to the Canvas information page for the course
ASTM29/NAAS003: Statistical Tools in Astrophysics, 7.5 credits
given by the Department of Physics.
Note: this page contains general information about the course. If you are a student on the course you have to log in to the canvas portal to the left. The course calendar and course stream on this page are not active.
ContentsIn this course you will learn about:
The detailed course goals can be found in the course plans (see below). |
(Image: NASA, ESA, and S. Beckwith (STScI) and the HUDF Team) |
General information
- Semester: autumn
- Study period: 1
- Level: master
- Language: English
- Forms of teaching: Lectures, exercises and self-study
- Assessment: Final take-home examination (33%), and written reports on exercises (67%)
- Grading scale: U-G-VG
- Course plan: in English and in Swedish
Course literature
- Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data. Ivezić et al, Princeton University Press. Lund University provides access to this book via JSTOR Links to an external site.
Teacher
- Alexander Mustill, alexander.mustill@fysik.lu.se
Schedule
The schedule for the course can be found on the page specific to this year's course.
Usually lectures are 13:15-15:00 on Tuesday; 15:15-17:15 on Wednesday; and 10:15-12:00 on Thursday.
Computing lectures are held jointly with the Dynamical Astronomy course, and are usually 13:15 Monday and 10:15 Thursday in the first two weeks of HT2.
A home exam will be given at the end of the course. A set of questions will be published on the web; answers are to be handed in via canvas within a week. In order to pass the course, the student must pass the exam as well as hand in acceptable reports on each of the four projects.