This weekend I continued to work on a lab software upgrade for one of the labs I work in. This is all part of an effort on my part to streamline sample analysis, automate as much as possible, and make the data reduction smoother and more versatile. For those of you who care, I am doing everything with LabView, my programming platform of choice. My first step in the process is to go through the existing sets of code, figure out what does what, and decide if I want to copy the process or change things around.
This got me thinking, again, about error propagation. Most of the significant errors in the existing code are dealt with appropriately, but there are some very easy ones that are just ignored. Truth is, most calculations are fairly easy to propagate errors through, and I am a firm believer that uncertainty must be dealt with honestly, even if in the end it is insignificant. The most popular geochronologic data reduction tool (I am guessing) is Ken Ludwig’s Isoplot. This does an excellent job with uncertainties, assuming of course the users report them all. But, Isoplot doesn’t interface with the machines, and it can only work with the data it is given.
For this reason I think that the book An Introduction to Error Analysis by John R. Taylor (a physicist from the University of Colorado) should be required for anyone who works in a lab or with the data from a lab. All of the basic methods to propagate uncertainties are covered and explained very well. This doesn’t discuss some of the more complicated methods common in geochronology (e.g. the MSWD), but for a starter and reference text it is well worth it. It also isn’t directed towards the earth sciences, but again, the basics are the basics. For example, to calculate the size and correct for the depletion of a spike or standard shot of gas, you need to know the reservoir tank and pipette volumes, and the pressure of the gas in the tank (partial pressure if your gas isn’t pure). Associating uncertainties with each of these measurements is fairly straightforward, so any number that comes out of these values, say size of spike, or a correction for ionization efficiency, should include those propagated uncertainties. Numbers without uncertainties really don’t exist in geology, but they show up in data reduction all the time.
Dealing with errors in a realistic and representative way is the first step. Getting people to report them, even when they are crappy, is the second.