PDC 402: Deeper Insights Into Understanding Exposure Variability and IH Statistics
Sun, 5/18: 8:00 AM - 5:00 PM CDT
P402
Professional Development Course
P402
Professional Development Course
Kansas City Convention Center
Room: 2102 A
CM Credit Hours: 7
Description
Is a group compliant with the OEL? What do 6 measurements tell about what happened the rest of the year? How do I convert measurement data into information about the AIHA exposure control categories? The variability observed in occupational exposures represents a considerable challenge to obtaining them reliably. There is a lack of practical tools to support day-to-day decision-making. This PDC includes 1) a primer on Bayesian statistics; 2) their application to industrial hygiene data interpretation; 3) data interpretation strategies; 4) approaches to interpret small samples and intermittent exposures; and 5) best practices for dealing with non-detects. The PDC provides a practical illustration of the above topics with Expostats, and IHSTAT_Bayes.
*Registration includes boxed luncheon. **Power strips will not be provided at each attendee's seat; however, laptop charging stations will be provided in each course room.
*Registration includes boxed luncheon. **Power strips will not be provided at each attendee's seat; however, laptop charging stations will be provided in each course room.
Course Outline
• Bayesian Statistics for Non-statisticians
• Bayesian Statistics for Industrial Hygiene
• Using Expostats and IHSTAT_Bayes
• Assessing the Statistical Performance of Sampling Strategies
• Treatment of Non-detects
• Rationale Underpinning the Interpretation of Small Samples
• Bayesian Statistics for Industrial Hygiene
• Using Expostats and IHSTAT_Bayes
• Assessing the Statistical Performance of Sampling Strategies
• Treatment of Non-detects
• Rationale Underpinning the Interpretation of Small Samples
Learning Outcomes
Upon completion, the participant will be able to:
• Explain the basic principles underlying Bayesian statistics.
• Leverage Bayesian statistics in IH data analysis.
• Discuss the sampling and data interpretation guidelines proposed in the U.S. and Europe.
• Interpret data reported below the limit of quantification.
• Describe the small sample interpretation in the use of state-of-the-art sampling strategies.
• Leverage Expostats to quantify exposure levels and evaluate the effect of an intervention.
• Explain the basic principles underlying Bayesian statistics.
• Leverage Bayesian statistics in IH data analysis.
• Discuss the sampling and data interpretation guidelines proposed in the U.S. and Europe.
• Interpret data reported below the limit of quantification.
• Describe the small sample interpretation in the use of state-of-the-art sampling strategies.
• Leverage Expostats to quantify exposure levels and evaluate the effect of an intervention.
Prerequisites
Attendees should attend PDC 105: Understanding Exposure Variability & IH Statistics – Essentials before taking this course.
Value Added
Participants will have used Expostats / IHSTAT_bayes to make exposure decisions, will be able to use other similar tools, and will possess the skillset necessary to complete the AIHA exposure decision registry exam.
Business Case/IH Value Statement
Traditional exposure statistics rely on confidence intervals and hypothesis tests to demonstrate overexposure, which is sometime not easy to grasp by decision makers. The methods described in the PDC will allow practitioners to better understand the measurement data they collect and better communicate their interpretation to management and employees.
Course Level
Intermediate
Learning Aids
Laptop
Scientific Calculator
Organizational Category
Corporation/Company
Primary Industry
All Industries
Topics
Computer/Mobile Apps and Tools
Hazard Recognition/Exposure Assessment
Risk Assessment and Management
Transfer of Knowledge
Hands-on demonstrations and practicum
Post course test
Practice exercises