Lecture 1: Introduction & Measures of Central Tendency, Slides, (Extra Material)

Lecture 2: Measures of Dispersion & Chebyshev’s Inequality, Slides, (Extra Material, Example)

Lecture 3: Normal Datasets & Correlation, Slides, (Correlation)

Lecture 4: Counting Principles, Slides, (Counting, P & C)

Lecture 5: Sample Space & Events, Slides, (Sample Spaces)

Lecture 6: Probability, Slides, (Conditional Probability, Multiplication Rule, Simulation)

Lecture 7: Bayes' Theorem, Slides, (Bayes' Rule, Monty Hall Problem, Examples)

Lecture 8: Random Variables, Slides, (Examples)

Lecture 9: Jointly Distributed Random Variables, Slides, (Joint PDF & CDF)

Lecture 10: Expectation and Covariance, Slides, (Simulation)

Lecture 11: Discrete Distributions, Slides, (Bernoulli & Binomial, Example, Link between Binomial & Poisson)

Lecture 12: Continuous Distributions, Slides, (Uniform, Exponential)

Lecture 13: Functions of a Random Variable, Slides, (Examples)

Lecture 14: Functions of a Random Variable and Normal Distribution, Slides, (Examples, Normal Distribution)

Lecture 15: Normal and Standard Normal Distributions, Slides, (Reading Normal Tables, z-scores)

Lecture 16: Distributions arising from Normal, Slides, Simulation, (Simulating Observations)

Lecture 17: Sampling Distribution with Known Population Parameters, Slides, Simulation, (CLT, Example)

Lecture 18: Sampling Distribution with Unknown Population Parameters, Slides, (t-distribution)

Lecture 19: Point and Interval Estimation, Slides, (Notes, CI for means)

Lecture 20: Point and Interval Estimation, Slides, (t-score, CI for proportions)

Lecture 21: Point and Interval Estimation, Slides, (CI for diff in means)

Lecture 22: Hypothesis Testing, Slides, (Test of means, Test of proportions)

Lecture 23: Errors in Hypothesis Testing, Slides, (Errors, Power)

Lecture 24: T-test and Paired T-test, Slides, (t-test, Paired t-test)