Course Preview | Decision Making and Risk Analysis from Texas Executive Education
3:27 min
29
Hello, I'm Britt Freund and I'd like to introduce you to the risk management elective that we're about to undertake together. There will be there faculty teaching on this program. One is myself, another is a friend and colleague of mine, Professor Eric Bickel, and another friend and colleague of mine, Professor Fred Beach. Together, the three of us are going to take a deeper dive into risk management, and attempt to explain some of the key ideas about how to make good decisions in the face of significant levels of uncertainty.
Let me tell you a little bit about what you're about to see as you encounter this course. Module 1, I will be doing that, is about risk taxonomy. And basically, it frames the entire risk course. It describes different levels of uncertainty, how you might approach those different levels of uncertainty, and talks about which techniques are appropriate for that level of uncertainty. Module 1 will be followed by a Module 2 called probability basics. And the idea here is to set you up for understanding discrete probability distributions, and especially this idea of Bayesian probability and using decision trees to calculate expected monetary value, and to work backwards and understand the value of information. Module 2 is a very important module because it forms the basic analytical tools that we'll be using in the rest of the modules. Module 3 is a deeper dive into decision trees and the value of information, following on from Module 2, but really going into some level of detail on how you actually carry out some of the analysis.
Based upon the first three modules, we're now ready to assess probabilities. Because one of the challenges anytime you're trying to make decisions within the face of a lot of uncertainty, is how to estimate the uncertainty, how to set ranges on the uncertainty. And in Module 4, we're going to talk about conditioning statements, and how to try to debias yourself so that your estimate is a valid range estimate for the range of values that a particular topic can take on. We'll then, with Module 5 come back, and Eric and I together will be walking through an example. It's a fairly crafted example about whether I should put solar panels on top of my house or not. And we'll be using the ideas from Module 1 to Module 4, to work our way through this problem.
Finally, to cap off the overall module, Professor Fred Beach will discuss bigger decisions than whether you're going to put solar panels on top of my house or not. He's going to be looking at a power plant investment, and understanding how to assess the probabilities, likelihoods, and uncertainties associated with a prospective power plant, and whether it makes economic sense. We believe collectively, these six modules will ground you in a disciplined, well-structured way for approaching risky decisions in the face of a lot of uncertainty.
Let me tell you a little bit about what you're about to see as you encounter this course. Module 1, I will be doing that, is about risk taxonomy. And basically, it frames the entire risk course. It describes different levels of uncertainty, how you might approach those different levels of uncertainty, and talks about which techniques are appropriate for that level of uncertainty. Module 1 will be followed by a Module 2 called probability basics. And the idea here is to set you up for understanding discrete probability distributions, and especially this idea of Bayesian probability and using decision trees to calculate expected monetary value, and to work backwards and understand the value of information. Module 2 is a very important module because it forms the basic analytical tools that we'll be using in the rest of the modules. Module 3 is a deeper dive into decision trees and the value of information, following on from Module 2, but really going into some level of detail on how you actually carry out some of the analysis.
Based upon the first three modules, we're now ready to assess probabilities. Because one of the challenges anytime you're trying to make decisions within the face of a lot of uncertainty, is how to estimate the uncertainty, how to set ranges on the uncertainty. And in Module 4, we're going to talk about conditioning statements, and how to try to debias yourself so that your estimate is a valid range estimate for the range of values that a particular topic can take on. We'll then, with Module 5 come back, and Eric and I together will be walking through an example. It's a fairly crafted example about whether I should put solar panels on top of my house or not. And we'll be using the ideas from Module 1 to Module 4, to work our way through this problem.
Finally, to cap off the overall module, Professor Fred Beach will discuss bigger decisions than whether you're going to put solar panels on top of my house or not. He's going to be looking at a power plant investment, and understanding how to assess the probabilities, likelihoods, and uncertainties associated with a prospective power plant, and whether it makes economic sense. We believe collectively, these six modules will ground you in a disciplined, well-structured way for approaching risky decisions in the face of a lot of uncertainty.
