EE 178/EE 278A : Syllabus

Here is a rough syllabus (precise schedule will depend on the progress in class, and suggestions/feedback are welcome).

  1. Probability spaces (September 24-October 10)

    1. Sample spaces.

    2. Probability law.

    3. Conditional probablity.

    4. Bayes rule.

    5. Independence.

    6. Basics of stochastic simulations.

  2. Random variables (October 15-November 7)

    1. Definitions.

    2. Pmf, pdf, cdf.

    3. Important probability distributions.

    4. Joint distributions.

  3. Expectation and linear estimation theory (November 12-14)

    1. Definition.

    2. Conditional expectation.

    3. Correlation and covariance.

  4. Limit theorems (November 19- December 3)

    1. Law of large numbers.

    2. Central limit theorem.

  5. Throughout the class, we will explore further concepts as examples/applications:

    1. Point processes.

    2. Markov chains.

    3. Bayesian networks.

Homeworks will be assigned on Thu, due on Thu of the following week. There will be an in-class midterm on Friday, November 1 and an in-class final exam.