Know what statistics CAN do for you, CANNOT do for you & how your project gets into TROUBLE if you don’t know the difference
There will be very few, if any, equations: this is NOT a statistical theory or software course! This is a “foundations” course for understanding when to apply which statistics to cleanup tasks.
Goals of this Workshop are to understand:
- Why are statistics used at all in environmental cleanup? For what cleanup decisions (e.g., establishing ARARs, site characterization, risk assessment, remedial design, long-term monitoring, NFA, etc.) can statistics be useful?
- What are the benefits AND limitations of applying statistics in cleanups?
- Basic statistical concepts and definitions.
- The fundamental mismatch between common statistical assumptions & cleaning up real-world contaminated sites.
- How the Triad framework provides a scientific foundation for correcting those mismatches, so statistics can be applied appropriately & transparently in the following contexts:
- Constructing a workable, realistic conceptual site model (CSM)
- Articulating project goals
- AKA: What questions are we trying to answer? And how much scrutiny & controversy will those answers/decisions have to withstand?
- Generating data to answer questions (How good does the data have to be?)
- Establishing data quality & decision confidence requirements
- Using real-time methods to address decision uncertainty via dynamic work strategies
- Leveraging collaborative data sets by coordinating different analytical methods within the sampling design
- Building collaborative data strategies into traditional and dynamic data collection programs
- Interpreting collaborative and real-time data set results
Instructors: Deana Crumbling, Stephen Dyment (USEPA Office of Superfund Remediation and Technology Information) and Robert L. Johnson (Argonne National Laboratory)
For general information contact Deana Crumbling
by telephone at 703-603-0643
or
via e-mail at crumbling.deana@epa.gov
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