• Stephen Biss

Uncertainty of Measurement is Not Novel Science


To obtain an admission from a CFS scientist that uncertainty of measurement is not novel science.

A. ...So, it’s a static measurement uncertainty where you use the results of the previous year. You take the average and you take the variability associated with that, and that is used to apply the analysis of the blood sample in this particular case, until the next year. So, we’ve just switched over to the 2016 M-U data, for 2017.

Q. You just used the words ‘measurement uncertainty.’ A. Correct, yes. Q. That’s a reasonable scientific concept in measurement? A. It is, yes. It’s one way of measuring the variability. But it’s a measurement of – the analysis of the standards as opposed to a measurement of the variability associated with the analysis of the subject’s blood sample. Q. Ah. All right. It’s based on.... A. Which is an average of the four analyses that were measured when that analysis was done. Q. It’s based on the control tests over a period of time; the historical control tests. A. Yes.


Q. So, those are the control tests that are associated with the analysis you’re doing for each of these subjects. A. Correct. And they apply to this analysis that was done there. Q. All right. A. The control data from the previous year is used to determine the measurement uncertainty. Q. All right. But next year, that control data will be used, the control data that you generated when you were doing your – say, a blood analysis, on Mr. H. The control – that control data will be used in the following year for calculating measurement uncertainty associated with that particular instrument.


Q. From the controls. A. With all different instruments that are used. There’s four different instruments that are used and there’s probably 18 different people who do alcohol analysis, so that variability would be associated with the various instruments as well as the people who are doing the analysis, as well as the pipets that are used, right? So, all that uncertainty from each of those different things that are used in the method go in to create the measurement uncertainty value. Q. All right, the point is you use historical data to generate that calculation of measurement uncertainty. A. That's correct.


Q. And that historical data relates to the control tests. A. Yes, from the previous year. Not the ones.... Q. And so, what – what – the steps that are taken in calculating that measurement uncertainty would be to take 50 control tests, total them, get an average. First step? A. Yes. Q. And then take that average and look at each of the individual – see how much control test number 3, what it’s – how much its result varies from the average. I just – I want to do what I can to try and explain standard deviation as best I can. And I’m going to need your help along the way, but basically, standard deviation is a kind of an average of the deviations of the control test results from their average. It’s an average of an average. An average of deviations. A. Yes. Q. And it’s always in a positive number, not a negative number... A. Well, it could be... Q. ...because deviations.... A. or minus. Q. Yeah, deviations can go either way. A. Correct. Q. That’s the whole point of them being standard deviations but in order to get that number, to come up with that number, for a standard deviation, you take an average of those? A. Yes.

#crossex #UM

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