Part 2: Random Variables
Computational Probability
Course overview
1
Tools of the data scientist
2
Parallel computing
Part 1: Probability
3
What is probability?
Part 2: Random Variables
4
Data types
5
Data summaries and visualizations in R
6
Summaries: Distributions and Samples
7
Combinatorics
8
Discrete random variables
9
Continuous Random Variables
Part 3: Estimation
10
Kernel density estimation
11
Method of moments
12
MLE
13
Intervals & Communicating uncertainty
HW + Deliverables
HW 4
HW 5
HW 8 - Discrete and continuous random variables
HW 9: Estimation
Exam 2 Prep
Exam 2
Part 2: Random Variables
3
What is probability?
4
Data types