An extension to the previous post on confidence intervals. This clarifies more explicitly some of the misconceptions, and interpretations. I also suggest that Land’s Exact approximation is unreliable (hopefully I’m wrong!).

An explanation of upper confidence limits of the arithmetic mean

The MVUE is just “the best mean”, right? Not necessarily. Read about exactly what an MVUE is and how it compares to to the other ways of estimating the arithmetic mean of lognormal data when performing statistics reviews in occupational hygiene.

Systems and tools in occupational hygiene do exactly what they were designed to do, though this may not always be what the user intended. These are a Golems of Occupational Hygiene.

A book review on Rappaport & Kupper’s “Quantitative Exposure Assessment”. A 2005 occupational hygiene centric statistics textbook. While challenging to follow at times for those without statistical background, it is a very interesting read to shape how you think about exposure assessments.

QQ plots are incredibly useful in learning about the distribution of your sampled data. You may have used these plots in your analysis before, but this post will dive a little deeper into how they are made so you can get the most out of them.

Censored data is an annoyance but a common occurrence in hygiene. While there is no consensus yet on the best method to treat censored data, one thing is clear: Substitution is Fabrication.

Markov Chain Monte Carlo is an algorithm that explores the parameter space of Bayesian calculations. It’s the engine tht makes otherwise impossible solutions reveal themselves step-by-step.

A reflection on how I think about idealistic principles of occupational hygiene in conflict with the priorities of business.

Exposure modelling is estimating exposure levels without investing in sample collection. While under-utilised in Australia, there are many user-friendly tools used to help in your preliminary exposure assessments. But caution is advisable.

Bayesian statistics is more intuitive than you may first think. This post gives you a feel for how Bayes’ theorem works and why you should be using it in occupational hygiene.

A reflection on my experience at the 2023 AIOH conference

A more robust rule of thumb that allows you to compare the largest value with the OEL to determine compliance with high levels of certainty.

How openly should we share the information we collect in exposure assessments? Are there limits? And what metrics should we use to tailor the communicated information to achieve the best outcome?

The OSHA silica table has been practically replicated in Queensland, Australia. Unfortunately, following the control requirements does not guarantee effective management of exposures.