Texts:
Probability: A Graduate Course, By Allan Gut, 2nd edition, Springer.
Recommended Texts:
Course Description: This is a graduate level introductory course to probability theory. In particular, we will cover: Introduction to probability with measure theoretic foundations. Fundamentals of measure theory. Probability space. Measurable functions and random variables. Expectation and conditional expectation. Zero-one laws and Borel-Cantelli lemmas. Chracteristic functions. Modes of convergence. Uniform integrability. Skorokhod representation theorem. Basic limit theorems.
Prerequisites: CAS MA 511; or consent of instructor.
Syllabus (tentative)
I will try to follow the syllabus as closely as possible. However it may change depending on our progress.
Any changes will be announced in class and posted here.
| Assingment | Due Date | Assignment | Material Covered |
| Date | Assignment | Material Covered |
| TBA | Midterm | TBA |
| TBA | Final | TBA |
Tentative grading policy: Your grade will be based on :(a) Homework (30%), (b) midterm exam (30%) and final exam (40%). The grading policy may change depending on the progress of the class.
Exam & Homeworks:
Exams: There will be one midterm exam and one final exam. The exam material for each one of the two exams will be announced in class and posted on the webpage of the course.
Homeworks: There will be several homeworks, both theoretical and more of applied flavor.
The due date of each homework will be announced in class and it will usually be 7-10 days after.
Late homeworks will NOT be accepted.
Make-up policy: Make up exams will be given only in extreme circumstances, and only when accompanied by appropriate documentation. Any student with a valid reason to be given a make up exam must contact me prior to the exam, either by email or in person, and present documentation at the next class session attended.