- Prepare (soft due Th 9/2, hard due M 9/13)
- Content below
- Sakai quizzes

- Group Worksheet (soft due F 9/3, hard due M 9/13)
- Practice (due M 9/13)
- Perform (due M 9/27)

## Content

2B.A – Foundations of Probability (52 min.)

- Outcomes, Events, Probabilities (15 min.)
- Joint and Conditional Probability (11 min.)
- Marginalization and Bayes’ Theorem (15 min.)
- Random Variables and Expectations (11 min.)

2B.B – Distributions of Random Variables (46 min.)

- Distributions, Means, Variance (19 min.)
- Monte Carlo Simulation (15 min.)
- Central Limit Theorem (12 min.)

## Optional Supplements

You can access an excellent free online textbook on OpenIntro Statistics here, co-authored by Duke faculty. You can pay a suggested but adjustable price for a tablet-friendly pdf, but you can also just get the regular pdf for free. For this module, the following optional readings may be particularly helpful supplements:

- Chapter 3: Probability. This provides more information on many of the topics from the above videos in Foundations of Probability.
- Chapter 4: Distributions of random variables. This provides much more information about particular classic distributions than is provided in 2B.B.1.
- Chapter 5.1: Point estimates and sampling variability. This provides more information on some of the topics from 2B.B.2-3.

In addition, you can find documentation for the two pseudorandom number generating / sampling libraries in python that we mentioned here:

- Python random – Base Python library
- Numpy random – Numpy random sampling library