Lecture Notes
Antoine Cerfon
CIMS, NYU
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Notes for undergraduate Probability and Statistics
Lecture 1: Outcomes, events, and probability
Lecture 2: Conditional Probability and Independence
Lecture 3: Discrete Random Variables
Lecture 4: Continuous Random Variables
Lecture 5: Expectation and Variance
Lecture 6: Computation with Random Variables
Lecture 7: Joint Distributions
Lecture 8: Covariance and correlation
Lecture 9: The Poisson process
Lecture 10: The law of large numbers and the central limit theorem
Lecture 11: Introduction to exploratory data analysis
Lecture 12: Estimation of parameters
Lecture 13: Maximum likelihood estimation