Which type of survey error might improve with repeated trials?

Random error is the type of survey error that might improve with repeated trials. These errors occur due to unpredictable fluctuations in the measurement process, such as variations in environmental conditions, operator inconsistencies, or limitations in measuring instruments. When multiple measurements are taken and averaged, the effects of these random errors tend to cancel each other out, resulting in a more accurate overall estimate. This is the essence of statistical averaging, which helps mitigate the impact of random variations inherent in each individual observation.

On the other hand, systematic errors are consistent and repeatable inaccuracies that stem from factors such as calibration issues or biases in the measurement process. These do not improve with repeated trials unless the underlying cause of the systematic error is corrected. Blunders are significant mistakes or human errors that are typically isolated incidents and do not improve with repeated measurements. Instrument errors relate to malfunctions or inaccuracies of the measuring devices themselves, which also require adjustment or calibration solutions rather than mere repetition to resolve.