Even with the advent of software to perform statistical calculations, it is important to understand the underlying concepts to properly interpret industrial hygiene data sets. Because of the uncertainty and variability in typical industrial hygiene data sets, there are common pitfalls in interpreting the data, even among experienced Certified Industrial Hygienists. This introductory presentation describes these pitfalls as well as the strengths and limitations of three common approaches to industrial hygiene data analysis: traditional statistics, Bayesian statistics, and rule-based data interpretation. Suggestions are offered to help decide which approach to use for a given data set.
Who Should attend?
From the laboratory bench chemist to manufacturing to management; including formulation development, project team, CMC members and QA, chemists, biologists and operators, Drug innovators, CMOs, and small to large pharma and biotech.
Dr. Brent Altemose, Ph.D., CIH, CSP is a Principal Industrial Hygienist with Trinity Consultants. Since beginning his career as a ventilation engineer, he has worked for over 20 years in the fields of industrial hygiene and occupational safety. Dr. Altemose has particular expertise in exposure control, exposure assessment strategies and modeling, analysis of industrial hygiene data, local exhaust and laboratory ventilation, and indoor air quality.
Note: The course fee is per attendee. Recording the training course is strictly prohibited.
For registration questions please contact Kent Rader at Kent.Rader@safebridge.com
Aug 27, 2020 -- Online
11:00 AM Eastern time