Using numbers and handling data
Using numbers and handling data

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Using numbers and handling data

2 Accuracy, precision and common errors

2.1 Differences between accuracy and precision

Accuracy is a measure of how close a result is to the true value. Precision is a measure of how repeatable the result is. For instance, a group of three friends tried the shooting gallery at a fair and their targets are shown in Figure 6. The first person was an expert marksman, but they were using a rifle with sights that had not been set properly. Although they aimed the sights at the bull's-eye they consistently hit the target off to the left side instead. They were not accurate, but they were precise. The second person was also an expert marksman, but noticed the incorrectly set sights and compensated by aiming to the right of the bull's-eye. Consequently, all their shots hit the centre of the target - they were both accurate and precise and their results were good. The third person was hopeless with the rifle and their shots landed all over the target - they were neither accurate nor precise.

Figure 6
Figure 6 Target practice analogy, demonstrating the difference between accuracy and precision. Low accuracy but high precision = systematic error. High accuracy and high precision = good results. Low accuracy and low precision = bad results

From the example given you can see how it is possible to be very precise, but not at all accurate. This is called a systematic error (sometimes also called bias) and can normally be corrected.

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