In an experiment, what does it mean if measurements are accurate but not precise?

The scenario described indicates that the measurements obtained are accurate but lack precision. Accuracy refers to how close the measured values are to the true or accepted value, while precision indicates the consistency and reproducibility of the measurements.

When measurements are close to the true value, but vary widely, this suggests that there is accuracy in the data obtained. However, because the values show a wide range, this leads to a lack of precision. In other words, the results do not consistently cluster around a particular value, resulting in a large spread between the measurements.

In contrast, other options relate to aspects of precision rather than accuracy. Consistently close measurements would indicate precision and not necessarily accuracy. A small range of values also implies that the measurements are tightly grouped, which indicates a high degree of precision. Finally, consistently leading to the same conclusion points towards precision as well, since it implies that the measurements yield similar results repeatedly. Therefore, the correct choice accurately describes the situation where measurements are accurate but not precise.