Statistics course for PhD students

Lectures topic list

Cheat sheet / notes

Lecture 1 : basic descriptive statistics

Lecture 1 - slides [pdf]

Lecture 1 - slides [keynote]

Lecture 1 - problem set

Lecture 2 : searching for correlations

Lecture 2 - slides [pdf]

Lecture 2 - slides [keynote]

Lecture 2 - problem set

Lecture 2 - Lemaitre (1927) dataset

Lecture 2 - Hubble (1929) dataset

Lecture 2 - Two distribution dataset

Lecture 3 : hypothesis testing and model-fitting

Lecture 3 - slides [pdf]

Lecture 3 - slides [keynote]

Lecture 3 - problem set

Lecture 3 - Model-fitting example dataset

Lecture 4 : Bayesian inference

Lecture 4 - slides [pdf]

Lecture 4 - slides [keynote]

Lecture 4 - problem set

Other resources

Useful textbooks:
Wall & Jenkins, "Practical Statistics for Astronomers", 2nd edition
Press et al., "Numerical Recipes"

David Hogg's article about line-fitting : http://arxiv.org/abs/1008.4686