Mathematical Astronomy

Benjamin L'Huillier
Sejong University
Spring 2024

Notebooks

1. Chapter 1 - Fundamentals of Probabilities
2. Chapter 2 - Continuous Probabilities
3. Chapter 3 - Estimation
4. Chapter 4 - Least Squares
5. Chapter 5 - Bayesian Inference
6. Chapter 6 - Hypothesis Tests
7. Chapter 7 - Resampling

Useful Resources

Intro to Python:

Here are some good resource to learn/improve your python skills:

• D. Green's Physics Lecture and Notebook
• K. Tadai's Astroinformatics Lecture
• D. Gerosa's Scientific Computing Lecture
• Khuyen Tran's Efficient Python tricks and tools for data scientists

Astrostatistics

• D. Gerosa's Astrostats 2024 Lecture: A great course! also 2022 and 2023
• C. Sabiu's Astrostats Lecture
• Python Datascience Handbook

General Statistics

• MIT 18.650 Statistics for Applications, Fall 2016 (YouTube)