Ever wondered if a sample’s chemical concentration is “normal” or unusually high? In this post, we dive into the science of analyzing chemical data, from understanding percentiles to using benchmarks like NHANES for comparison. Whether you’re investigating environmental contaminants or studying health trends, knowing how to interpret data can make all the difference.

An article from the CBC addressing per- and polyfluoroalkyl substances – known as PFAS - from an environmental and biomonitoring standpoint within Canada recently popped on my feed. What stood out was that numbers were being presented without any context to which compound was measured and/or relationship to what a background versus industrial range is.

This article, although a large media source, fell into a few pitfalls of presenting technical information to the public. These pitfalls stem from innaccuate data visualizations and uncredible presentation of quantitative information. Within this recent blog, I lay out the noticable discrepancies and present updated visualizations that help to shed more information on the data.

Stephen Hawkins was quoted to say ”Observation which deviates so much from other observations as to arouse suspicion it was generated by a different mechanism”. However how do we put some objectivity into this subjective topic?

As an eager beaver myself sometimes I want to jump quickly into the world of statistics, but sometimes understanding how the distribution of numbers fluctuates can save you a world of time.

In forensic applications, a cosine theta (cos-Ɵ) similarity metric that can be used to compare two histograms by treating each isomer distribution as a multi-dimensional vector, and to calculate the cosine of the angle (Ɵ) between the two vectors.

One of the key traits that distinguished the consulting work I’m a part of is the ability to refine complex and technical academic literature into accessible applications for industry partners. The geoforensic work on oil weathering patterns through a GC×GC perspective highlights the ability to distill complex information to help assess real oil spill and emergency spill response situations.