Lecture 1 - Tutorial - How to Install Octave and using Octave
Lecture 2 - Background and relevance
Lecture 3 - Examples of managing uncertainty and making decisions
Lecture 4 - Risk, uncertainty and variability
Lecture 5 - Probability: Events, Conditioning and Total Probability
Lecture 6 - Discrete random variables
Lecture 7 - Continuous random variables: characterisitcs and examples
Lecture 8 - Expected Value: Mean, Variance and Functions
Lecture 9 - Multiple Random Variables: Discrete and Continuous
Lecture 10 - Criteria, Objectives and Settings for Decisions
Lecture 11 - Introduction to one-time decisions
Lecture 12 - Solving the secretary problem
Lecture 13 - Which option to gamble just once?
Lecture 14 - Utility Function
Lecture 15 - Nested one-time decisions
Lecture 16 - Decision Trees
Lecture 17 - Decisions in Game Shows: Final Jeopardy
Lecture 18 - Decisions in Game Shows: Monte Hall
Lecture 19 - Project Network and Analysis
Lecture 20 - Newsvendor Problem: Background, Model and Analysis
Lecture 21 - Newsvendor Problem: Example and Proof
Lecture 22 - Buffers to Cushion for Fluctuations
Lecture 23 - Safety Stock for Inventories
Lecture 24 - Safety Stock: Example and Derivation
Lecture 25 - Route Planning
Lecture 26 - Exploration and Exploitation
Lecture 27 - Introduction to sequential decision making
Lecture 28 - Costs, Ratings, Options and Choices for both Restaurants
Lecture 29 - Two Stage Stochastic Optimization
Lecture 30 - Concluding Remarks and Simpson's Paradox
Lecture 31 - Markov Chains for Decisions
Lecture 32 - DTMC Modeling and Analysis
Lecture 33 - Markov Decision Process Set Up
Lecture 34 - Analyzing the four policies
