Probability
Axioms, conditioning, random variables, distributions, and expectation.
Axioms, conditioning, random variables, distributions, and expectation.
This course expects complete reasoning: definitions and hypotheses are stated, manual arguments remain visible, computation is labeled as exact or approximate, and conclusions are interpreted rather than merely reported.
Course outcomes
- Model sample spaces and derive probabilities from axioms and counting arguments.
- Use conditional probability, independence, and Bayes reasoning precisely.
- Analyze discrete and continuous random variables and distributions.
- Compute and interpret expectation, variance, and simulation error.
Prerequisites
advanced-algebra