From the college website... In this module you will have the opportunity to:
- use probability theory to model uncertainty
- design simple probabilistic models that facilitate prediction
- conduct sound scientific analysis of data
- use Bayesian inference to refine hypotheses
This module covers the following topics:
- Foundations of probability based on measurable sets
- Discrete random variables and their probability distributions
- Poisson processes
- Continuous random variables and their probability distributions
- Central Limit Theorem
- Generating functions
- Joint random variables
- Estimation
- Hypothesis Testing
- Bayesian inference
- Markov chains
Probability (First Half): Professor Giuliano Casale Statistics (Second Half): Professor Chiraag Lala.