What type of error is described as "errors of estimation"?

Random errors, often referred to as "errors of estimation," arise from unpredictable fluctuations in measurements during data collection. These errors are typically caused by uncontrollable factors or inherent variability in the measurement process. For instance, slight changes in environmental conditions, timing of measurements, or even individual differences in technique can lead to random errors.

As these errors do not consistently occur in the same direction, they can result in measurements that scatter around the true value, making it difficult to pinpoint an accurate estimation. Over many trials, the influence of random errors can average out, leading to more reliable results, but they remain an inherent part of the experimental process.

This definition and understanding differentiate them from the other types of errors listed. Systematic errors are consistent and predictably skew measurements in one direction, while human errors typically stem from a person's mistakes or misjudgments during experimentation. Instrument errors are linked to flaws in the measuring devices used. Thus, the characterization of random errors as "errors of estimation" aligns with their nature of being variable and unpredictable.