Classifying types of error with the error table

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There a number of different ways to classify errors. Below, we present two classifications: (a) Analytical vs Sampling and (b) Systematic vs Random) and give examples of each

 

	Analytical errors - errors due to instrument uncertainty	Sampling errors - errors due to random fluctuations in the medium being measured and errors due to inadequate siting of instruments
Systematic error – bias, reproducible error	Calibration offsets – (e.g. offset in pressure sensor or linear sensor drift)	Poorly sited instruments (e.g. temperature measurements tend to be close to cities and may be influenced by urban heat island effect)
Random error – non‑reproducible error	Random noise in an instrument (e.g. variable power supply to an instrument causing random variations in its sensitivity)	Random fluctuations in the measurement medium (e.g. errors in the estimation of mean temperature in the atmospheric boundary layer caused by turbulent variations)