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Quantitative Risk Assessment Methods: Model Building

This course provides participants with the opportunity to construct actual quantitative risk assessment models, while providing more in-depth training in the complexities and practicalities of quantitative methodologies. Building on knowledge from the Probabilistic Methods course, Quantitative Methods: Model Building teaches techniques for building and linking distributions so the complexity of multi-faceted problems can be reduced to a level that we can understand and explain to decision makers. Participants are encouraged to bring their own data, on-going or re-visited assessments, and ripe food safety problems to the course. Student teams will form around these activities, and simple quantitative risk assessment models will be constructed. Team and individual efforts may be saved on disk for further refinement after the course. Participants can expect to become more competent with the @Risk™ software tool.

The course is conducted in a computer teaching laboratory. Lectures describe various techniques.  Students then work individually or in groups to solidify their understanding of the lecture materials, and to begin to build quantitative skills.

We strongly recommend Introduction to Food Safety Risk Assessment and Quantitative Methods: Probabilistic Methods as prerequisites to this course.

Overview of Topics

Modeling Overview

  • What is a model?
  • Types of Models
  • Simulations
  • Spreadsheet Modeling Techniques
  • Modeling Process

Probabilistic Scenario Analysis

  • Why Decisions are Hard
  • Scenario Types and Comparisons
  • Event Tree Construction
  • Incorporating Probability into Scenario Analysis

Sensitivity and Importance

  • What is Sensitivity Analysis?
  • How to do Sensitivity Analysis
  • Importance Analysis
  • Systematic Investigations

Sampling

  • Populations and Samples
  • Representativeness
  • How to take a sample
  • Chance
  • Estimating Intervals

Model Dependencies

  • Monte Carlo Warning
  • Model Flaws
  • Dependency Assumptions
  • System  Modeling Approaches

Presenting Risk Assessment Results

  • Packaging Your Results
  • Knowing your audience
  • Telling the story
  • Good graphics

Learning Objectives

After completing this course, students understand:

  • The importance of the right question
  • What models are and some of the commonly used types of models
  • Basic spreadsheet modeling techniques
  • Scenarios and event trees
  • Why variability and uncertainty are endemic in risk assessment
  • What sensitivity analysis is and the reasons for doing it
  • How to assure representativeness
  • The basic concept of inferential statistics
  • The risks of inadequate understanding and handling of dependencies
  • Techniques for handling dependencies
  • Generating information from risk assessment results

This course meets a requirement of the JIFSAN Quantitative Track Certificate in Food Safety Risk Analysis.

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JIFSAN
University of Maryland
0220 Symons Hall
College Park, MD 20742
E-mail: jquigley@umd.edu
Tel.: (301) 405-1696 Fax.: (301) 405-8390
 

 

University of Maryland JIFSAN