PDC 401

Bayesian Statistics: Overview and Applications in Industrial Hygiene Data Interpretation

intermediate | 8 CM Credits/ 0.8 CEU/COC/ 0.5 CMP
Sunday | 8:00 a.m. – 5:00 p.m.
Limit: 60

Exposure Assessment Strategies, Risk Assessment & Management

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The Bayesian statistical framework offers exciting opportunities for improving the accuracy, efficiency, and transparency of our exposure judgments. Bayesian techniques can be used to formally combine our professional judgment regarding a particular exposure and its uncertainty along with the statistical analysis of current exposure data. The language and framework of the approach holds promise for expressing the output of exposure assessments in a manner that is much more easily understood and communicated than the output from more traditional statistical analysis. Best of all, the Bayesian decision analysis approach formalizes traditional exposure assessment processes already used by industrial hygienists today. This PDC will provide an overview of the Bayesian framework for decision analysis and explore, through discussion and workshops, opportunities for its application in IH data interpretation and exposure risk assessment.

Value Added:

Receive software for performing Bayesian decision analysis calculations and participate in workshops on formalizing the exposure assessment process.


Familiarity with A Strategy for Assessing and Managing Occupational Exposures. Experienced in exposure assessments and monitoring data interpretation.

Learning Aids:

Participants must bring a laptop


Upon completion, the participant will be able to

  • Implement techniques for improving the accuracy of their exposure judgments.
  • Relate a Bayesian framework for decision analysis to the AIHA® Exposure Assessment Strategy.
  • Use a software tool to perform Bayesian decision analysis of IH monitoring data.


  • Making Good Exposure Decisions: Interpreting Data
  • Importance of Professional Judgment
  • AIHA Exposure Assessment Model: Inherently a Bayesian Approach
  • Improving Judgments: Bayesian Decision Analysis (BDA) Theory and Tool
  • Putting Improvement Ideas to Practice: Scenario Examples
  • Use of Subjective Decisions
  • Integrating Improvement Activities into Your Professional Practice

Topic Areas of Focus:

  • Exposure Assessment Strategies
  • Risk Assessment & Management 

Transfer of Knowledge:

Instructors will evaluate participants understanding of the materials presented based on

  • Hands-on demonstrations and practicum,
  • Practice exercises, and
  • Group activities.

Instructors: John Mulhausen, 3M Company, St. Paul, MN; Kevin Wallace, Exxon Mobil, Houston, TX; Perry Logan, 3M Company, St. Paul, MN; Gurumurthy Ramachandran, University of Minnesota, Minneapolis, MN; Paul Hewett, Exposure Assessment Solutions, Morgantown, WV; Tim Blodgett, 3M Company, St. Paul, MN

Sponsoring Committee: Exposure Assessment Strategies

Online Course Evaluation: https://www.surveymonkey.com/s/ZDMV7D8


Have you taken this course? Share your thoughts.

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  1. AIHce 2012 Attendee

    Awesome course. More reinforcement during the year would help highlight the importance of using statistical tools and calibrating professional judgment.

  2. AIHce 2012 Attendee

    Nice interactive course with valuable basic statistical knowledge geared toward IH. Great course!

  3. AIHce 2012 Attendee

    Good practice questions and it was quite useful to have an actual copy of the software. Good course.

  4. AIHce 2012 Attendee

    Course is very applicable and on trend. I wouldn’t really change a thing. I would be interested in knowing how to stay in touch or in tune with advances in this area and updated and continued validation of software and models.

  5. AIHce 2012 Attendee

    John M demonstrated not only his breadth of knowledge, but delivered the curse material with a high level of enthusiasm and commitment to enhancing the profession.

  6. AIHce 2012 Attendee

    I wouldn’t change a thing! In the 20 years I have been taking courses, this is by far one …if not THE best I have taken thus far!