"A good science and engineering decision is a good business decision."


Decision Precision training and consulting

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Advanced Decision Analysis
with Portfolio and Project Modeling (ADA)
Prerequisites

Persons planning to register for ADA should have attended Petroleum Risk and Decision Analysis (PRD) and have learned most concepts. Alternatively, people are invited to attend ADA with equivalent experience.

We expect participants in ADA arrive with the following background:

  • Experienced in setting up and solving decision trees
  • Knows the fundamentals of Monte Carlo simulation, including Latin hypercube sampling
  • Understands these popular statistics: mean, median, mode, variance and standard deviation
  • Can calculate present values without using an NPV function
  • Familiar with common decision criteria, especially: NPV, IRR and EMV
  • Proficient with Microsoft® Excel in a Windows environment. The participant should be fluent in using IF statements.
  • Can apply the four fundamental probability rules: complement, addition, multiplication, and Bayes' rules
  • Understanding the decomposition of decision policy: objective, time value, and risk aversion.

Additionally, participants will be aided with any prior experience in economic evaluation, such as by attending either Basic Petroleum Economics (either short or expanded versions) or Economics of Worldwide Petroleum Exploration taught by Richard Seba and colleagues.

People coming to ADA prepared with this knowledge will find the course more enjoyable and rewarding (as will their colleagues). If you are unsure about your knowledge level, we suggest that you complete the self-assessment (and fun!) Pre-ADA Self-Assessment Quiz.

Strong English skills are important for this class.  Excel, add-in decision analysis software, and the Windows operating system will be in English.

Depending upon interest, persons attending PRD and ADA in successive weeks can arrange to meet with the instructor during the weekend between courses for review and answering questions.

In ADA you will learn

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