ST3009: Statistical Methods for Computer Science 2018-19

Module descriptor

Lectures: Weds 3-5pm LB01
Tutorials: Weds 1-2pm LG12
Lecturer: Doug Leith
Tutorial Assistants: Goksu Yamac

Quick survey

The module is a first course in probability and statistics that only assumes basic mathematical (algebra, sets) and programming (we'll use matlab) knowledge. The aim is to take students to the point where they have the foundation needed for understanding machine learning techniques (and so for a follow on module on machine learning or to read an introductory book), performance analysis of computer systems etc.

The module is divided into four parts (each roughly three weeks long) and the topics covered in each part are summarised here.

Assessment is 70% final exam, 20% mid-term exam (held directly after reading week) and 10% marked weekly questions.

Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
Week 8
Week 9
Week 10
Week 11
Week 12