When is a GPS measurement considered to have low accuracy but high precision?

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Multiple Choice

When is a GPS measurement considered to have low accuracy but high precision?

A GPS measurement is considered to have low accuracy but high precision when the measurements consistently fall close to each other, but are consistently incorrect relative to the true value. This situation implies that there is a repeatable process or source of error affecting the GPS readings, resulting in a narrow range of measurement results that do not reflect the actual location. For instance, if a GPS receiver consistently provides measurements that are all 10 meters off from the true location in the same direction, the precision is high because the repeatability of the measurements is good—the results are tightly clustered together. However, the accuracy is low because those measurements are still incorrect. This scenario helps highlight the difference between accuracy (how close a measurement is to the true value) and precision (how consistently measurements can be replicated). High precision but low accuracy is often observed in situations where systematic errors are present in the dataset or measurement technique.

A GPS measurement is considered to have low accuracy but high precision when the measurements consistently fall close to each other, but are consistently incorrect relative to the true value. This situation implies that there is a repeatable process or source of error affecting the GPS readings, resulting in a narrow range of measurement results that do not reflect the actual location.

For instance, if a GPS receiver consistently provides measurements that are all 10 meters off from the true location in the same direction, the precision is high because the repeatability of the measurements is good—the results are tightly clustered together. However, the accuracy is low because those measurements are still incorrect.

This scenario helps highlight the difference between accuracy (how close a measurement is to the true value) and precision (how consistently measurements can be replicated). High precision but low accuracy is often observed in situations where systematic errors are present in the dataset or measurement technique.

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