General Risk Analysis

Duration: 5 full days

Minimum of 6 people and maximum of 20

Course overview

This course is designed for those people who already have some experience in risk analysis modeling a Monte Carlo simulation package for Excel such as @Risk or Crystal Ball, but wish to extend that knowledge.

The course provides an in-depth explanation of various concepts and techniques necessary for superior level risk assessments. Prior knowledge of the material covered in the Quantitative Risk Analysis course or equivalent, together with significant experience in risk modeling, will be needed.

The course is designed to encourage the modeler to develop creative problem solving skills to ensure that their analyses are decision-focused, accurately, efficient and the results presented in a manner that provides decision makers with the clearest and most helpful input

Duration: 5 full days

Workshop overview

This is a workshop for risk analysts who are already very accomplished in the mathematical modeling of risk, and/or who have risk modeling problems that they wish to discuss amongst peers.

Duration: 4 full days

Minimum of 6 people and maximum of 15

Course overview

This 4-day course will cover the core principles of quantitative risk analysis and the most important risk modeling principles, methods and techniques. The course will be taught using the R statistical language but the lessons apply equally well to other modeling environments. The focus of the course is on how to conduct accurate and effective quantitative risk analyses, including best practices of risk modeling, selecting the appropriate distribution, using data and expert opinion, and avoiding common mistakes. The course will also cover essential probability and statistics theory and various stochastic processes to provide the participants with a solid understanding of quantitative risk analysis.

Duration: 4 full days

Minimum of 6 people and maximum of 15

Course overview

This 4-day course will cover the core principles of quantitative risk analysis and the most important risk modeling principles, methods and techniques. The course will be taught using the R statistical language but the lessons apply equally well to other modeling environments. The focus of the course is on how to conduct accurate and effective quantitative risk analyses, including best practices of risk modeling, selecting the appropriate distribution, using data and expert opinion, and avoiding common mistakes. The course will also cover essential probability and statistics theory and various stochastic processes to provide the participants with a solid understanding of quantitative risk analysis.

Duration: 3 full days

Minimum of 6 people and maximum of 20 people

The Quantitative Risk Analysis (QRA) course is designed to provide participants with a practical overview and foundation of the use, approaches and diverse applications of quantitative risk analysis in supporting improved decision-making.

Course overview

• Learn and practice the main principles and techniques in quantitative risk analysis (QRA);
• Understand how to employ QRA to better understand risk and uncertainty and improve decision-making;
• Learn to work with risk analysis modeling environments (in this case @RISK, Risk Solver or Crystal Ball with Excel, but the lessons apply equally well to other modeling environments);
• Learn how to conduct accurate and effective quantitative risk analysis, including best practices of risk modeling, selecting the appropriate distribution, using data and expert opinion, and avoiding common mistakes, while also discussing how to use QRA in decision-making;
• Gain expert insight from EpiX Analytics’ vast experience consulting to large and small organizations worldwide.