The precision of an instrument has a direct impact on measurement uncertainty; greater precision results in lower uncertainty.

In physics, precision refers to the degree of exactness or accuracy with which a measurement is conducted. This concept is closely tied to uncertainty, which quantifies the doubt or variability associated with a measurement. When an instrument exhibits higher precision, it yields measurements with reduced uncertainty.

To illustrate this, consider two rulers: one that measures to the nearest millimeter and another that measures to the nearest centimeter. If you use the millimeter ruler to measure the length of a table, your measurement is precise to $\pm 1 \text{ mm}$. In contrast, using the centimeter ruler will yield a precision of $\pm 1 \text{ cm}$. In this scenario, the uncertainty associated with the measurement using the millimeter ruler is significantly less than that with the centimeter ruler due to its higher precision.

Instruments designed with higher precision aim to minimize random errors in measurements. Random errors are fluctuations that occur unpredictably when the same quantity is measured multiple times. These errors are inherently linked to the instrument’s precision: the smaller the random errors, the greater the precision of the instrument, and consequently, the lower the measurement uncertainty.

Furthermore, precision can also influence systematic errors, which are consistent, repeatable errors that arise from faulty equipment or flawed experimental design. A lack of precision in an instrument can lead to the introduction of systematic errors, thereby increasing overall uncertainty in the measurements.

In summary, the precision of an instrument is vital in determining the uncertainty of a measurement. Higher precision correlates with lower uncertainty. Therefore, in experiments where high precision is essential, it is crucial to utilize instruments that offer the greatest precision possible to effectively minimize uncertainty.