EE 342

Modules Topics covered in this class

For any module not marked as “Coming Soon”, click on it to go to a page containing details.

Introduction to EE 342

1. Introduction to EE 342

Overview of EE 342, and some simple initial tasks to get oriented and ready for the course. View the full comic here. Syllabus here

Mon, Aug 21 - Mon, Aug 21
Sets, Logic and Functions

2. Sets, Logic and Functions

The picture you see represents the construction of a Cantor set, which you can learn about in the (optional) experiential learning section of this module.

Wed, Aug 23 - Sat, Aug 26
Probability Space

3. Probability Space

The photo you see is of Andrey Kolmogorov. who fundamentally transformed probability theory (and many other areas). His academic career started as an editor of his school journal at the age of 5, where he noticed that the first \(n\) odd numbers sum to \(n^2\).

Sun, Aug 27 - Sat, Sep 2
Conditional Probabilities and Independence

4. Conditional Probabilities and Independence

Given the pic above, is this a cat or a dog?

Sun, Sep 3 - Thu, Sep 9
Bayes Theorem

5. Bayes Theorem

Bayes Theorem in a seashell (Credit: xkcd.com)

Fri, Sep 8 - Tue, Sep 12
Random Variables

6. Random Variables

Random Variables

Wed, Sep 13 - Sun, Sep 24
Bernoulli and Friends

7. Bernoulli and Friends

Bernoulli and Binomial random variables. The picture is Pascal’s triangle made of binomial coefficients, eponymous with the random variable that captures number of successes in a fixed number of independent Bernoulli trials.

Mon, Sep 25 - Mon, Oct 2
Geometric and Poisson

8. Geometric and Poisson

Geometric and Poisson random variables. Extends the independent Bernoulli trials when the number of trials is not fixed in advance. Pic: chewing gum stains on sidewalk, number of stains per tile is approximately Poisson. Pic source: Wikipedia

Wed, Oct 4 - Fri, Oct 13
Continuous Random Variables: Exponential

9. Continuous Random Variables: Exponential

Continuous random variables, pdfs, distribution functions, expectation and variance. Exponential random variables, used most famously in radiocarbon dating. Pic: Glencoe boabab, dated by radiocarbon dating to be \(\approx\) 2000 years old.

Mon, Oct 23 - Tue, Oct 31
Conditional Expectation

10. Conditional Expectation

Conditional Expectation

Wed, Nov 1 - Thu, Nov 9
Gaussians

11. Gaussians

Basics of Gaussian Random Variables, univariate and multivariate.

Fri, Nov 10 - Wed, Nov 22