- Lecture 1: Introduction and statistical sins
- Lecture 2: Is it Gaussian?
- Lecture 3: Bayesian statistics 1, parameter estimation for discrete distributions
- Lecture 4: Bayesian statistics 2, parameter estimation for continuous distributions
- Lecture 5: Bayesian statistics 3, model comparison
- Lecture 6: Fitting a straight line to data part 1: no uncertainties on independent variable
- Lecture 7: Fitting a straight line to data part 2: uncertainties in both variables
- Lecture 8: Are two quantities correlated?
- Lecture 9: Are two distributions different from each other?
- Lecture 10: Markov chain Monte Carlo samplers
- Lecture 11: Kernel density estimation and k-d trees
- Lecture 12: A quasi-Bayesian goodness of fit test

Coding exercises and data sets:

- No coding in advance of the first class
- Coding exercise for class 2 (5 February 2018)
- Coding exercise for class 3 (12 February 2018). Associated data set 1, data set 2, data set 3, and data set 4
- Coding exercise for class 4 (19 February 2018). Associated data set
- Coding exercise for class 5 (26 February 2018). Associated data set 1, data set 2, data set 3, and data set 4
- Coding exercise for class 6 (5 March 2018). Associated data set
- Coding exercise for class 7 (12 March 2018). Associated data set
- Coding exercise for class 8 (26 March 2018). Associated data set
- Coding exercise for class 9 (2 April 2018). Associated data set 1, data set 2, data set 3, data set 4
- Coding exercise for class 10 (9 April 2018). Associated data set
- Coding exercise for class 11 (16 April 2018). Associated data set
- Coding exercise for class 12 (23 April 2018). Associated data set
- Coding exercise for class 13 (30 April 2018). Associated data set