In general, systematic errors cause a bias in measurements that result in an ‘offset’ of measured data points from the ‘true’ value of the quantity being measured. Systematic errors are commonly ...

In this article, AHN Biotechnologies explains how to avoid common pipetting errors for better lab results.

Non-sampling errors fall under two categories: random and systematic. Random errors are believed to offset each other and therefore, most often, are of little concern.

The subtypes and examples of errors are discussed, as follows: Random Errors – Random errors are not mathematically or statistically predictable, nor are they generally able to be corrected. They are ...