Explore the fundamental concepts and applications of Maximum Likelihood Estimation (MLE) in this 30-minute lecture. Delve into the basics of MLE before examining practical examples using various probability distributions. Learn how to apply MLE to binomial scenarios, revisit the binomial example for deeper understanding, and then progress to Poisson and uniform distribution applications. Gain valuable insights into this powerful statistical technique from Professor Knudson's concise yet comprehensive presentation.
Overview
Syllabus
1. Maximum Likelihood Estimation Basics.
2. MLE Example: Binomial.
3. MLE Example: Binomial Revisited.
4. MLE Example: Poisson.
5. MLE Example: Uniform.
Taught by
Professor Knudson
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