Welcome to the canvas information page for the course

ASTM29: Statistical Tools in Astrophysics, 7.5 credits

given by the Department of Astronomy and Theoretical 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.

Contents

In this course you will learn about:

Basic probability theory and statistics.

The concept of probability, probability distributions, and Bayes' theorem.

Sampling, moments, correlation, order statistics, and graphical presentation of data.

Estimation of parameters and model fitting.

The principle of Maximum Likelihood and least-squares method.

Signal, noise, errors, and uncertainties.

The detailed course goals can be found in the course plans (see below).

The Hubble Ultra Deep Field

(Image: NASA, ESA, and S. Beckwith (STScI) and the HUDF Team)

General information

Semester: autumn
Study period: 2
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

Teachers

Paul McMillan (Course responsible, email: paul@astro.lu.se, phone: 046-222 7312)
Daniel Mikkola (Computing lectures, email:mikkola@astro.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.

Application

Through antagning.se