Uncertainty components

Standard deviation – an important component of uncertainty

Several components make up total measurement uncertainty, and one of the most important is standard deviation, so let’s discuss that next.

A simple, yet worthwhile practice is to repeat a measurement/calibration several times instead of just performing it once. You will most likely discover small differences in the measurements between repetitions. But which measurement is correct?

Without diving too deep into statistics, we can say that it is not enough to measure once. If you repeat the same measurement several times, you can find the average and the standard deviation of the measurement and learn how much the result can differ between repetitions. This means that you can find out the normal difference between measurements.

You should perform a measurement multiple times, even up to ten times, for it to be statistically reliable enough to calculate the standard deviation.

These kinds of uncertainty components, which you get by calculating the standard deviation, are called A-type uncertainty components.

But repeating the same measurement ten times is just not possible in practice, you may say.

Luckily you don’t always need to perform ten repetitions, but you should still experiment with your measurement process by sometimes repeating the same measurement several times. This will tell you what the typical deviation of your whole measurement process is, and you can use this knowledge in the future as an uncertainty component related to that measurement, even if you only perform the measurement once during your normal calibration.

Imagine that when performing a temperature measurement/calibration multiple times, you learn that there is a ±0.2 °C difference between the repetitions. Next time you perform the same measurement – even if you only perform it once – you would be aware of this possible ±0.2 °C difference, so you could take it into account and not let the measurement get too close to the acceptance limit.

If you calibrate similar kinds of instruments repeatedly, it is often enough to perform the measurement just once and use the typical experimental standard deviation.

In summary, you should always be aware of the standard deviation of your calibration process – it is an important part of the total uncertainty.

Your reference standard (calibrator) and its traceability

One of the biggest sources of uncertainty often comes from the reference standard (or calibrator) that you are using in your measurements / calibrations.

Naturally, to start with you should select a suitable reference standard for each measurement.

It is also important to remember that it is not enough to use the manufacturer’s accuracy specification for the reference standard and keep using that as the uncertainty of the reference standards for years.

Instead, you must have your reference standards calibrated regularly in a calibration laboratory that has sufficient capabilities (a small enough uncertainty) to calibrate the standard and to make it traceable. Pay attention to the total uncertainty of the calibration that the laboratory documents for your reference standard.

Also, you should follow the stability of your reference standard between calibrations. After some time, you will learn the true uncertainty of your reference standard and you can use that information in your calibrations.

Other sources of uncertainty

In the white paper you can find more detailed discussion on the other sources of uncertainty.

These include:

• Device under test (DUT)

• Reference standard (calibrator)

• Method/process for performing the measurements/calibrations

• Environmental conditions

• The person(s) performing the measurements

• Additional uncertainty components depending on the quantity being measured/calibrated

These uncertainty components are referred to as type B uncertainty components.