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