Which factor can incorrectly suggest that a measurement is accurate when it is merely precise?

Bias is a systematic error that indicates a consistent deviation of measured values from the true value. When measurements are precise, they may yield results that are very close together, showing high repeatability. However, if there is a bias present, it means that these precise measurements could all be consistently wrong.

For instance, if a scale is biased due to a calibration error, multiple readings could appear accurate because they are consistent (precise) with one another, but they could still be far removed from the actual weight being measured. Thus, while the precision of the measurements may suggest accuracy, the presence of bias negates this assumption, leading to the incorrect conclusion that the measurement is valid.

In contrast, the other factors like speed, cost, and calibration involve different aspects of the measurement process but do not directly reflect the inherent relationship between accuracy and precision related to systematic errors.