Modeling Food Safety and Animal Health Risks Using R - (Online)
Duration: 16 hours over a two-week period
Time per day: 1-2 hours
Grading requirements: Attendance at live lectures and review of all core course materials
This online course provides an essential introduction to risk analysis and quantitative risk modeling for food safety and animal health. Exercises and problems will demonstrate core risk analysis functionality and applied food safety and animal health models in R, an open-source software platform. The class combines live sessions led by experienced instructors with self-paced lectures and practical problems to solve. Each topic will include a mixture of lectures, supporting reading material, demonstration of software implementation, and practice problems to solve. EpiX Analytics is an international leader in providing training, consulting, and research in performing risk analysis. Our instructors provide real-life context to theory based on decades of consulting experience in the fields of animal health, food safety, and health risk analysis. Case studies from previous real projects will be presented and discussed to illustrate the combination of various concepts introduced in the course.
Who should attend?
This course is geared towards anyone interested in the foundational concepts of quantitative risk analysis. The course context, and therefore the subject of most of the problems and examples, will be animal health and food safety, but the principles and procedures taught are applicable to risk analysis problems of all types. Previous experience with R software is not required.
- Duration: 16 hours over a two-week period
- Time per day: 1-2 hours
- Grading requirements: Attendance at live lectures and review of all core course materials
- Software required:
- Course participants will have access to all course materials starting on the first day of the class. The seven live sessions below will also be recorded for asynchronous viewing, and will be held 8-9am US Mountain Daylight Time UTC/GMT - 6 hours the following days:
- Introduction to the course and instructors (Day 1)
- Discussion: Introduction to risk analysis, statistical foundations, simulation in R (Day 3)
- Discussion & Refresher: Binomial Process (Day 4)
- Discussion & Refresher: Poisson Processes (Day 5)
- Discussion & Refresher: Fitting distributions (Day 6)
- Discussion: modeling uncertainty (Day 8)
- Course wrap-up and review (Day 10)
- Introduction to Risk Analysis
- Fundamentals of Statistics for Risk Analysis: probabilities, visualization, most useful probability distributions
- Communicating Results of a Risk Analysis: plots, statistics, sensitivity analysis
- Risk Analysis in R: probability calculations and efficient simulation, outputs
- Stochastic Processes: Binomial, Poisson, aggregate modeling
- Fitting Distributions: sourcing data, assessing fit
- Using Expert Opinion: modeling techniques
- Correlations: copulas and more
- Modeling parameter uncertainty: classical, bootstrap and Bayesian methods
- Dose Response Modeling: chemical and microbial
Please contact us to obtain a code for the discounts below. Discounts for groups of 3 to 10 people are applied automatically at registration. Discount rates cannot be combined.
|* Early registration - 10% off registration (register and pay 30 days before course start date)|
|* Government/Academic - 5% off registration (Proof of eligibility requested after registration)|
|* Student - 25% off registration (Proof of eligibility requested after registration)|
Use our contact form if you are interested in a course not currently in our schedule.
|Start Date||October 19, 2020|
|End Date||October 30, 2020|
|Cut off date||October 15, 2020|