Educational Material for Mathematics and Statistics
Educational material for mathematics and statistics available for download for private use.
Main Coursebook
Introduction to Statistical Methodology
Comprehensive lecture notes for a course on introductory statistics. A separate book of practice exercises to accompany these lecture notes can be found on this page. [490 pp.]
Exercises with Solutions
Exercises for Introduction to Statistical Methodology
Extensive set of practice exercises with solutions. These range from technical exercises to extended project-style applications involving real data. These are cross-tabulated with the main coursebook. [305 pp.]
Main Coursebook
Intermediate Statistical Methodology
Comprehensive lecture notes for a course on intermediate statistical methodology. The coursebook contains an extensive set of practice exercises with solutions. These range from technical exercises to extended project-style applications involving real data. A separate archive of demonstration software to accompany these lecture notes can be found on this page. [604 pp.]
Software Files
Software files for Intermediate Statistical Methodology
An archive of R software files to accompany Intermediate Statistical Methodology. These contain fully coded applications of the methods described in the main coursebook. [zipped archive of 20 R files]
Study Notes
A compact summary of introductory topology. [49 pp.]
Study Notes on Topology
Study Notes
Operations Research
Includes dynamic programming and utility theory. These are fairly old, but I hope still useful. [61 pp.]
Study Notes
Causal Inference and Bayesian Networks
Summary of the basic theory of Bayesian networks, and their relationship to causal inference. [55 pp.]
Lecture Slides
Causal Inference and Bayesian Networks
A version of the Causal Inference and Bayesian Networks study notes in lecture slide format. [80 pp.]
Lecture Slides
Advanced Theory of Statistical Inference
Lecture slides for a graduate level course 0n the theory of statistical inference (large sample inference is not included in this course) [zipped archive contains 22 files of lecture slides, with a separate legend file]