Introduction to Probability
Prerequisite Background Material (Revision)
Set theory, Counting, Combinatorics, Probability space, Axioms
Lectures
Part I: Introduction to Probability
- Lecture 1: Conditional probabilities and Bayes’ theorem
- Ross: Chapter 3.1-3.5
- Dekking: Chapter 3.1-3.4
- PDF file at the end of this page
Part II: Random Variables
- Lecture 2: Random variables, probability mass function, expectation
- Ross: Chapter 4.1-4.4
- Dekking: Chapter 4.1-4.2
- PDF file at the end of this page
- Lecture 3: Expectation properties, variance, discrete distributions
- Ross: Chapter 4.5-4.6
- Dekking: Chapter 7.1-7.6, 4.3, 4.5-4.6
- PDF file at the end of this page
- Lecture 4: More discrete distributions: Poisson, Geometric, Negative
- Ross: Chapter 4.7-4.8
- Dekking: Chapter 4.4-4.6
- PDF file at the end of this page
- Lecture 5: Continuous random variables
- Ross: Chapter 5.1-5.5
- Dekking: Chapter 5.1-5.3, 5.5, 5.7-5.8
- PDF file at the end of this page
- Lecture 6: Marginals and Joint Distributions
- Ross: Chapter 6,7.4
- Dekking: Chapter 9,10
- PDF file at the end of this page
- Lecture 7: Independence, Covariance and Correlation
- Ross: Chapter 6,7.4
- Dekking: Chapter 9,10
- PDF file at the end of this page
Additional Exercises
Some exercises from Ross's book for lectures 1-4: PDF
Some additional exercises: PDF
Solutions to some Exercises can be found under the Supervisors Tab