Share Description
In this course, you will learn:
- How to think about randomness and uncertainty.
- How to make accurate forecasts.
- Understanding random variables via the lens of a storey.
- In statistics and data science, common probability distributions are utilised.
- Methods for determining a random quantity's expected value.
- How to address difficult situations with conditional probability
Syllabus:
- Introduction, Course Orientation, and FAQ
- Probability, Counting, and Story Proofs
- Conditional Probability and Bayes' Rule
- Discrete Random Variables
- Continuous Random Variables
- Averages, Law of Large Numbers, and Central Limit Theorem
- Joint Distributions and Conditional Expectation
- Markov Chains
