{"id":70923,"date":"2022-09-01T06:25:45","date_gmt":"2022-09-01T06:25:45","guid":{"rendered":"https:\/\/www.dewetron.com\/news\/what-types-of-measurement-errors-are-there\/"},"modified":"2026-09-20T02:42:40","modified_gmt":"2026-09-20T02:42:40","slug":"what-types-of-measurement-errors-are-there","status":"publish","type":"post","link":"https:\/\/www.dewetron.com\/us\/news\/what-types-of-measurement-errors-are-there\/","title":{"rendered":"What types of measurement errors are there?"},"content":{"rendered":"
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If there is one dogma that every metrologist, engineer or scientist is familiar with, it is probably the following: The statement of a (physical) measurement result without the statement of a measurement error is worthless.\u00a0<\/em><\/p>\n

As harsh as this statement may sound, it is true. Every measuring device and every measurement contains sources of error. The specification of a measurement error (measurement uncertainty) provides information about the quality of the measurement and its specification is absolutely necessary. For example, if the result of a voltage measurement is 5 V \u00b1 3 V, the true value of the voltage can be as high as 8 V or as low as 2 V. If one omits the measurement uncertainty, it is not possible to give any information about the deviation of the measured value from the true value.<\/p>\n

In practice, however, it is actually the case that one omits statements of measurement uncertainties completely. This is simply because the uncertainties are assumed to be irrelevantly small. Nevertheless, one should always be aware of this. Yet, measurement uncertainties do not imply a shortcoming or are a negative criterion. They should rather be seen as a kind of quality assurance, which allows a certain evaluation of the measured value (and points to potential improvement possibilities).<\/p>\n

In measurement technology, there are different types of measurement errors. The two most significant are the systematic <\/em>measurement uncertainties and the random (statistical)<\/em> measurement uncertainties. In this blog post, we will go into more detail about what distinguishes these two types of uncertainties.<\/p>\n\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/div>\n\n\n

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Systematic measurement uncertainties<\/h2>\n
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Systematic measurement uncertainties, sometimes referred to as built-in errors<\/em>, are uncertainties that occur systematically. This means, they lead to a shift of the measurement result in a specified direction. This shift is also called offset<\/em>.<\/p>\n

An example of systematic measurement errors is a mechanical clock that, due to a construction flaw, always ticks a little too fast. Therefore, if you use this watch to stop for example a marathon, you will always get a wrong result. However, this result can be easily adjusted since it is of a systematic nature. If it is possible to find out this systematic deviation, e.g. by comparing the mechanical clock with a more accurate atomic clock, one can simply correct the measured value. In the technical language one calls this adjustment<\/em><\/a>.<\/p>\n

In many cases, however, one is sure that the own measuring device has been adjusted correctly. Nonetheless, other systematic measurement errors can occur. To avoid these, one must be aware of the underlying causes. There are many causes for systematic measurement errors. You can find some of them in the following list:<\/p>\n