by Geoffrey G. Decroue
Outline of the course
1. Foundations of Probability Theory (Week 1)
Lectures Part 1
Class 1
Class 1 solutions
Axioms of PT
2. Discrete RVs (Week 2)
Lectures Part 2
Class 2
Class 2 solutions
3. Continuous RVs (Week 3)
Lectures Part 3
Class 3
Class 3 solutions + tutorial
Pareto distribution
4. Multivariate RVs (Week 4/5)
Lectures Part 4
Class 4
Class 4 solutions
Class 5
Class 5 solutions
5. Convergence of RVs (Week 6)
Lectures Part 5
Class 6
Class 6 solutions
6. Elements of Statistical inference (Week 7/8)
Lectures Part 6
Class 7
Class 7 solutions
Class 8
Class 8 solutions
7.* Extra Bonus
Extra Exercises
Extra Solutions
Assessment
Assignment 1 - till 10:00am 19th september
Assignment 1 solutions
Assignment 2 - till 10:00am 10th october
Assignment 2 solutions
Assignment 3 - till 10:00am 24th october
Assignment 3 solutions
3 assignments (every two weeks - you will get your first assignment at the end of
Week 2), worth 20% of your final mark.
1 final exam, worth 80% of your final mark.
References
We will not follow a textbook in particular, but you may find these references useful:
W. Feller (1957). An introduction to probability theory and its applications (Volume 1). John
Wiley & Sons.
F.M. Dekking, C. Kraaikamp, H.P. Lopuha•a, L.E. Meester (2005). A Modern Introduction to
Probability and Statistics: Understanding Why and How. Springer.
Y. Suhov, M. Kelbert (2005). Probability and Statistics by Example: Volume 1, Basic
Probability and Statistics. Cambridge.
R. Deep (2006). Probability and Statistics with Integrated Software Routines. Academic Press.