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Probability and Statistics – Class 1

Lesson 16: Exponential Distribution

We introduce the Exponential distribution, which is characterized by the memoryless property.

Lessons

Lesson 1: Probability and Counting
Lesson 2: Story Proofs, Axioms of Probability
Lesson 3: Birthday Problem, Properties of Probability
Lesson 4: Conditional Probability
Lesson 5: Conditioning Continued, Law of Total Probability
Lesson 6: Monty Hall, Simpson’s Paradox
Lesson 7: Gambler’s Ruin and Random Variables
Lesson 8: Random Variables and Their Distributions
Lesson 9: Expectation, Indicator Random Variables, Linearity
Lesson 10: Expectation Continued
Lesson 11: The Poisson distribution
Lesson 12: Discrete vs. Continuous, the Uniform
Lesson 13: Normal distribution
Lesson 14: Location, Scale, and LOTUS
Lesson 15: Midterm Review
Lesson 16: Exponential Distribution
Lesson 17: Moment Generating Functions
Lesson 18: MGFs Continued
Lesson 19: Joint, Conditional, and Marginal Distributions
Lesson 20: Multinomial and Cauchy
Lesson 21: Covariance and Correlation
Lesson 22: Transformations and Convolutions
Lesson 23: Beta distribution
Lesson 24: Gamma distribution and Poisson process
Lesson 25: Order Statistics and Conditional Expectation
Lesson 26: Conditional Expectation Continued
Lesson 27: Conditional Expectation given an R.V.
Lesson 28: Inequalities
Lesson 29: Law of Large Numbers and Central Limit Theorem
Lesson 30: Chi-Square, Student-t, Multivariate Normal
Lesson 31: Markov Chains
Lesson 32: Markov Chains Continued
Lesson 33: Markov Chains Continued Further
Lesson 34: A Look Ahead
Lesson 35: Joseph Blitzstein: “The Soul of Statistics”

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