| Course Outline: |
-
Sample spaces, events, axioms of probability (Ch. 2)
-
Some elementary combinatorics. Combinations and permutations (Ch. 1)
-
Conditional probabilities, independence and Bayes Formula (Ch. 3)
-
Discrete random variables (Ch. 4) and Continuous random variables (Ch. 5)
-
Joint distributions, marginal distributions and conditional distributions (Ch. 6)
-
Expectation: sums, covariance, moment generating functions (Ch. 7)
-
Limit Theorems: weak law of large numbers, central limit theorem (Ch. 8)
You can find a course syllabus here.
|