Statistics AN II
Statistics AN I
In the era of data science the responsible, principled and accurate use of statistics is of very high importance. You will learn about the foundations of probability theory and statistics with a special focus on applications to astronomical research.
This course introduces common topics in statistical modeling, including:
Missing data problems
You will apply the learned methodology during practical classes by solving exercises using both analytical computations and programming with Python.
The main objective of this course is to give you an overview of statistical tools and methodology which is commonly used in astronomy and physics research. After this course, you will be able to:
Answer basic questions on the following statistical topics: hypothesis testing, regression, and missing data.
Carry out a detailed analysis of astronomical data using analytical reasoning and Python programming.
Develop critical thinking about statistical data analysis (e.g. you will be aware of possible pitfalls and be able to detect inaccurate or incomplete analysis)
In this course, students will be trained in the following behaviour-oriented skills:
Problem solving (recognizing and analyzing problems, solution-oriented thinking)
Analytical skills (analytical thinking, abstraction, evidence)
Structured thinking (structure, modulated thinking, computational thinking, programming)
Complex ICT-skills (data analysis, programming, simulations, complex ICT applications)
Written communication (writing skills, reporting, summarizing)
Critical thinking (asking questions, check assumptions)
Integrity (honesty, moral, ethics, personal values)
Mode of instruction
Interactive case studies on astronomical applications
- Tsake-home assignment
Lecture notes (distributed via Brightspace)
All of Statistics. Larry Wasserman (corrected second printing, 2005), ISBN 9780387402727. Click title to download electronic version through Leiden University Libraries.