Subject: Help with uncertainty calculations From: "Paul Chamberlain" To: "ISO Guide 25 Discussion (E-mail)" Date: Wed, 19 Apr 2000 17:31:50 -0600 We are a small laboratory preparing for our assessment to Guide 25. We are in the process of reevaluating and recalculating our uncertainties. Whenever we calibrate a test item we take several measurements (from 3 to 10). In our case it takes the majority of the time to setup the calibration and it is relatively easy to take several readings. Each measurement is in fact a separate calibration repeated under the same setup under the "same" conditions. Obviously there is some variation in the data and we calculate and report the average. We also calculate the standard deviation and the data must fall within "limits" which are a % of the standard deviation compared to the average. What is the best/recommended way to use this data (short term noise) to estimate and report a standard uncertainty that will then be combined with other standard uncertainty estimates? We are already estimating several Type B uncertainties that can be theoritically correlated to environmental conditions, uncertainties of reference standards and measurement equipment. In addition, we estimate an uncertainty that accounts for long term drift which is obtained using control charts. Thanks for your intput. Paul Chamberlain LACO Technologies, Inc. 1-800-465-1004 paulc@lacotech.com www.lacotech.com -----snippo------------- Date: Thu, 20 Apr 2000 16:17:18 -0700 From: "Dr. Howard Castrup" To: Greg Gogates Subject: RE: Help with uncertainty calculations Raul, It sounds like you're doing a very thorough job in estimating uncertainties. Ordinarily,the variation in the data you mentioned is referred to as "random error." With regard to how to handle the random error standard deviation computed from a sample of data, it depends on whether you will be reporting the mean value obtained from the sample or are attempting to "characterize" the random uncertainty for individual values obtained with your measurement process. If you are reporting the mean value, you equate the random error standard uncertainty with the random error standard deviation divided by the square root of the sample size. If you are characterizing your process, you equate the standard uncertainty with the standard deviation as computed from your data. It is not likely that the random error in your process is correlated with other sources of error (e.g., measurment system bias, operator bias, environmental bias, etc.). If this is so, you can simply combine the random error standard uncertainty in rss with other uncertainties. If the random error in your process is correlated with one or more other measurement errors, you need to take the correlations into account. I hope this helps. Howard Castrup President, Integrated Sciences Group