Healthy Indoors Magazine

HI-September 2017

Healthy Indoors Magazine

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COVER STORY— September 2017 8 I t sometimes amazes me how people go about doing testing for indoor air quality surveys and then interpreting the data that they collect. Of- ten, individuals will approach a problem with their own preconceived notions on what is causing the issue, and then go about doing testing to prove that they are correct. For in- stance, say you have a building where some of the occupants are complaining about allergies, watery eyes and upper respiratory irritation. An IAQ consul- tant then comes to the building, find a couple of wa- ter stained ceiling tiles with suspect microbial growth and concludes that it's obviously a mold problem. He then goes about collecting a few spore trap sam- ples, along with maybe a tape lift sample or two from the ceiling tiles. The tape lift sample results come back showing that there is mold growth present (no duh) and the air sample results indicate that Asper- gillus/Penicillium counts for the two samples that he collected inside are slightly elevated compared to the single outdoor sample that he took as he left the building. Based on those results, the IAQ consultant proclaims that, yes indeed, what we have here is a mold growth problem and you need to remove the ceiling tiles and HEPA vacuum the entire area. Folks, let me tell you right now that this is just plain wrong. When it comes to hypothesis testing, as Beatrice in the Esurance commercial says, "That's not how it works. That's not how any of this works." By centering on a single con- cern, and performing sampling that only focuses on trying to prove that that particular issue is the culprit, you have completely ignored all the oth- er potential contributing factors. In the example above, which is based on an actual problem that I was involved in years ago, the real culprit was pet dander that was being brought in on a new em- ployee's clothing – not a couple of water stained ceiling tiles. It seems that the woman was a real cat lover (she had something like a dozen or so at By Jack Springston, CIH, CSP, FAIHA Performing an Indoor Air Quality Assessment home!) and several of her co-workers were quite allergic to cats. So, how do we go about doing valid hypothesis testing for indoor air quality surveys? Well, in order to do so, we first need to understand the concept of the null hypothesis and what types of errors we may encounter when doing our testing. Testing and the Null Hypothesis In either statistics or observational data, the null hy- pothesis generally refers to a default position that there is no relationship or correlation between two different observed or measured singularities. Typi- cally, the null hypothesis is assumed to be true until, and unless, evidence indicates otherwise. Testing is then performed, not to prove that the null hypothesis is correct, but rather to try and disprove - or nullify (hence the name 'null') - the hypothesis. Depending

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