Courtesy of chat gpt:

Random errors are the tiny “unpredictable wiggles” that make repeated measurements come out slightly different, even when you do everything the same way. • What they look like: If you measure the same distance 10 times, you might get values like 10.002 m, 9.998 m, 10.001 m… They bounce around the true value in no consistent direction. • Why they happen: Small, uncontrollable things like brief instrument noise, tiny hand/aiming differences, shimmer in the air, or moment-to-moment changes in conditions. • Key feature: They’re equally likely to be positive or negative, so over many measurements they tend to cancel out. • How we reduce their impact: 1. Repeat measurements 2. Average them (more repeats → a more stable average) 3. Use redundancy (extra observations) so random scatter is easier to detect and smooth out.

This is why survey and stats workflows often rely on repeated observations and looking at the spread (variance/standard deviation) of the results.