All measurements are subject to error. Error can be classified as human error or technical error. Perhaps you are transferring a small volume from one tube to another, and you don't quite get the full amount into the second tube because you spilled it: this is human error. Or perhaps you are using a scale that is improperly calibrated and reads 0.5 g with nothing on it. All measurements from that scale would therefore be overestimated by 0.5 g. This is a technical error.
It is important to both minimize error and to report the uncertainty associated with all measurements. The reason we care so much about significant figures is because they allow us to honestly reflect the uncertainty of measured values. We can convey uncertainty using something called absolute error. Absolute error is the difference between the measured value and the true (or accepted) value. Scientists use the absolute error in a measurement to quantify its uncertainty. This is often called the absolute uncertainty and is reported as ± with the measurement.
The absolute uncertainty is the number which, when combined with a reported value, gives the range of values in which the “true value” of the measurement sits. For example, a length may be reported as 5.3 mm ± 0.2 mm. In this case, the reported value is 5.3 mm, and the absolute error is 0.2 mm. The range of true values is 5.1 mm to 5.5 mm.
How do scientists describe the difference between a measured value and the true value?
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They use absolute error, which is the difference between the measured value and the true or accepted value. |
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