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Advanced Python & Statistics in Astronomy (2018)

ECTS credits: 6


Course parameters:

Language: English

Level of course: PhD course

Time of year: January/February 2018

No. of contact hours/hours in total incl. preparation, assignment(s) or the like: 50/150-180 hours

Capacity limits: 5 participants


Objectives of the course:

This course reviews the theory and implementation of Bayesian statistics and Markov chain Monte Carlo (MCMC) methods and offers an in-depth understanding of different data analysis tools related to astronomy using Python.

Learning outcomes and competences:

At the end of the course, the student should be able to:

  • Describe and discuss the background on Markov chains and subjects such as the Markov Chain Monte Carlo (MCMC) technique, Metropolis and Metropolis-Hastings algorithms, Gibbs sampling, prior/posteriors and Maximum Likelihood Fitting.
  • Analyse posteriors of an astronomical dataset using the MCMC python package ”emcee.py”, including making a model for the Maximum Likelihood and feeding ”emcee.py” with priors.
  • Code different tools in Python relevant for astronomy, e.g.: Normalization of data, handling of noise from the Earth’s atmosphere, interpolations, using stellar atmosphere model templates.
  • Use these different tools in Python to code a program that goes from an absolute raw dataset (model from instructor) to a dataset that is ready to be analysed. This should be submitted to the course instructor. 

Compulsory programme:

Participation in seminars and exercises


Course contents:

Weekly seminars and exercises



MA in physics or equivalent


Name of lecturers:

Dr. Carolina von Essen


Type of course/teaching methods:

Seminars, exercises



Title: “Data Analysis, A Bayesian Tutorial”, author: D.S. Sivia, Oxford Science Publications


Course homepage:



Course assessment:

Present and critically discuss an astronomical paper, which uses the above-mentioned statistical subjects and/or python implementation.



Department of Physics and Astronomy


Special comments on this course:




Mondays: 10-12, Wednesdays: 10-12, Thursdays: 10-12



Ny Munkegade 120, bygning 1520. Room number to be announced.



Deadline for registration is 12 January 2018.

If you have any questions, please contact Simon Albrecht or Carolina von Essen, e-mail:albrecht@phys.au.dk or cessen@phys.au.dk

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