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Statistics math is full of jargon - but useful

A project log for Climate & Environment Monitoring Station

Create a monitoring station to measure weather, soil, seismic, solar, magnetic, and gravity conditions - focus best accuracy/dollar w/COTS.

sparks.ronsparks.ron 10/23/2018 at 23:110 Comments

It has taken me a lot longer to understand the accuracy specifications of the various sensors I need to compare and/or choose from.  A lot of this is because the manufacturers leave details out of the datasheet when they specify accuracy. For example is the ± 0.1 ºC an absolute accuracy, a standard error, or what? And if they bin their sensors to fall within that accuracy, what sample standard deviation is allowed, etc.

Thankfully Sensirion has that information available if you dig deep enough. It will not show up on a Google search or a search of their website.  However, I did finally find it in the certification part of the Quality Control section of their website.  From what I can understand, they use a 95% confidence error on a sample group to generate their specified tolerance.  Hooray for Sensirion! They are doing things right and I can now use their sensors with reasonable expectations of repeatability and proper accuracy estimates.

This all is a bit esoteric and unnecessary for a simple home weather station. But since this project is aiming for a station that has calculable uncertainties, it is quite important. For example, each of the various sensors (e.g., pressure, humidity, temperature, etc.) generally output temperature.  Each has a different error band though.  By having statistically calculable error bands, all of these temperatures can be statistically compiled with a specified confidence interval and that will improve the station readings dramatically.

All of that means better accuracy with a lower cost.

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