Astronomy: Statistical Tools in Astrophysics

This course covers key statistical techniques used in astronomy and astrophysics, as well as other scientific fields. You will learn about how to extract meaningful information from uncertain data – a common problem in all areas of science. You will learn how to quantify the uncertainty in your inferences, and what uncertainty actually means in the two major schools of statistics, frequentist and Bayesian.

The course covers data visualisation and interpretation, how to fit a model to data, how to choose between two competing models, and how to evaluate the quality of a model fit. You will cover tools like Maximum Likelihood Estimation, Monte-Carlo methods, and periodograms to detect patterns in time series data.

You will explore both the theory behind these tools, and how to use them in practice. Statistics is a vast field, and by covering the theoretical background you will equip yourself to progress to, and critically evaluate, more advanced tools in statistics and machine learning in your future studies and careers. Meanwhile, you will gain practical experience via computational projects focusing on real-world applications, with examples drawn from astrophysical research (both contemporary and historical examples).

Teaching includes lectures and related in-class activities, and short computational projects. The focus in the lectures is on understanding the theoretical concepts: both the broad theoretical underpinnings of the different schools of probability theory and statistics, and the theory behind the specific tools you will use in the projects.

In the projects, you will write your own computer programmes to analyse data using the statistical methods covered in the lectures. You will receive feedback on your code write-up, time planning and results throughout the course.

Assessment is based on written reports from the computational projects, and a final written exam. Your final grade is based on both components, with the projects weighted more heavily.

Entry requirements

To be admitted to the course, students must have 75 credits in Physics and 45 credits in Mathematics, or a Bachelor of Science in Physics, and English 6/B.

Selection criteria

Seats are allocated according to: ECTS (HPAV): 100 %.

Tuition fees for non-EU/EEA citizens

Citizens of countries outside:

• The European Union (EU)
• The European Economic Area (EEA) and
• Switzerland

are required to pay tuition fees. You pay an instalment of the tuition fee in advance of each
semester.

Tuition fees, payments and exemptions

Full programme/course tuition fee: SEK 23,125
First payment: SEK 23,125

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Note that you may also need to pay an application fee, or provide proof of exemption.

Application fee

No tuition fees for citizens of the EU, EEA and Switzerland

There are no tuition fees for citizens of the European Union (EU), the European Economic Area (EEA) and Switzerland.