Advanced Methods in Applied Statistics 2018

Lecturer: D. Jason Koskinen
Email: koskinen (at)

Basic Information


Course Syllabus

The course is 100% likely to change once we begin, and future lectures listed below serve as an outline. Even so, we are very likely to cover the following topics which may require additional software support:

Class notes will be posted here:

Class 0 - Pre-Course

Class 1 Start (Feb. 6)

Class 2 - Monte Carlo Simulation & Least Squares (Feb. 8)

Class 3 - Introduction to Likelihoods and Numerical Minimizers (Feb. 13)

Class 4 - Intro. to Bayesian Statistics & Splines (Feb. 15)

Class 5 - Background Subtraction and sPlots (Feb. 20)

Class 6 - Markov Chain(s) (Feb. 22)

Class 7 - Parameter Estimation and Confidence Intervals (Feb. 27)

Class 8 - Hypothesis Testing (March 1)

Class 9 - Statistical Hypothesis Tests (March 6)

Class 10 - Presentations and Multivariate Analysis techniques (March 8)

The following lecture will be covered on March 15 in the afternoon. It had to be postponed due to the in-class student presentations and follow-up discussions.

Class 11 - Data Driven Density Estimation (non-parametric) (March 13)

Class 12 - Confidence Intervals, Failures, and Feldman-Cousins (March 15) Note that because of the change in schedule, this will be a long day with activities and course material probably using all the time from 09:00-12:00 and 13:00-17:00. Bring snacks!

Class 13 - Nested Sampling, Bayesian Inference, and MultiNest (March 20)

Class 14 - Work on Project (no lecture or new material)

Class 15 - Course Review, Discussion on Frequentist and Bayesian concepts, and Non-Parametric Tests Lecture snippet (April 3)

Extra Projects of a more difficult nature, for those who want something more challenging.