Math 1108-R17 Lecture 15 - Linear programming examples; What are Sets
Math 1108-R08 Lecture 15 - Counting examples; What is Probability and how to do it!
Math 1108-R17 Lecture 22 - More on Counting -- Harder examples!
Math 1108-R17 Lecture 29 - Binomial Probabilities; Probability Distributions; Expected Value
Math 1108-R17 Lecture 23 - Intro to Probability: Definition, Axioms, Compliment, and Disjunction
Math 1108-R17 Lecture 30 - Probability Distributions; Expected Value; and Binomial Probability
Math 1108-R17 Lecture 0 - Class Intro
Math 1108-R17 Lecture 24 - Solving probability problems and intro to Conditional Probability
Math 1108-R17 Lecture 34 - Practice problems: Markov Chains; Absorbing chains; Bayes' Theorem
Math 1108-R17 Lecture 27 - Probability examples: Bayes' Theorem; Birthday problem; Choosing balls
Math 1108-R17 Lecture 3 - Future Value of Annuities; Sinking Funds
Math 1108-R17 Lecture 32 - Regular Markov Chains; Steady state matrices; Long-term predictions
Math 1108-R08 Lecture 16 - Techniques for probability; Conditional Probability; Independent events
Math 1108-R08 Lecture 18 - More Probability - Bayes; The Birthday Problem; Independence
Math 1108 2 1 Distance and Midpoint
Math 1108-R08 Lecture 13 - Probability Teasers; Multiplication Rule; Permutations
Math 391 Lecture 16 - Higher Order Linear ODEs, after spring mass examples
Math 1108-R08 Lecture 19 - Binomial Probabilities; Probability Distributions; Expected Value
Math 1207-V21 Lecture 17 - Sketching Ellipses and Hyperbolas; Calculus, Areas, and Lengths of Polar
160B Lecture 15. Part 1. All continuous-time Markov chains look like this.
