Course Information This handout contains important information about the course.
A syllabus can be found on the official school page for the course here.
The list of key learning objectives describes the most important things you should learn from the course (it is NOT a substitute for the full syllabus).
Thanks to those who took the time to fill in the module questionnaire. You can see a statistical summary here and read my responses to the main points made here
Information concerning the mid-term test, the revision class and my office hours for Reading Week can be found here
2010/11 mid-term test solutions
2010/11 mid-term test feedback
numerical solutions for 2006/7 mid-term test
numerical solutions for 2007/08 mid-term test
numerical solutions for 2008/9 mid-term test
numerical solutions for 2009/10 mid-term test
Information concerning the end of term test
2010-11 End-term Test 2010-11 End-term Test Solutions2010/11 end-term test feedback
2009-10 End-term Test 2009-10 End-term Test Numerical SolutionsYour own lecture notes are the definitive guide to what is in the course. Anything lectured which is not explicitly described as non-examinable may appear in the test or exam. The notes which will appear below as the course progresses are a summary only of what was lectured. They are a modified version of notes given by Robert Johnson when he taught this module in 2008. They should be a useful guide to the most important concepts and results. However, they are do not contain all of the examples or explanation I gave in lectures. These are NOT a substitute for your own notes.
Week 1 (Sample Space and Events, Sets) Week 2 (Sequences and Functions) Week 3 (Probability, Proofs and Elementary Logic) Week 4 (Sampling) Week 5 (Independent Events, Conditional Probability) Week 6 (Conditional probability) Week 8 (Introduction to Random Variables, Discrete Random Variables) Week 9 (Discrete Random Variables, Some Common Discrete Probability Distributions) Week 10 (Joint Distributions of Discrete Random Variables) Week 11 (Cumulative Distribution Functions, Continuous Random Variables) Week 12 (Some Common Continuous Probability Distributions)The phrase book (of basic words and symbols of higher mathematics)
Peter Cameron's list of mathematical notation
Some other terminology - Theorems, Lemmas etc.
The next link is to a free online textbook with lots of exercises.Introduction to Probability, by Charles M. Grinstead and J. Laurie Snell
The next link is to Peter Cameron's detailed notes for a previous version of the course. Be warned that the material was slightly different and was covered in a slightly different way. The notation used is also different in some places.
Peter Cameron's notes on probability
2007/08 main exam, numerical solutions