3.1 Systematic Errors
Systematic errors are uncertainties in the bias of the data. A simple example is the zeroing of an instrument such as a voltmeter. If the voltmeter is not correctly zeroed before use, then all values measured by the voltmeter will be biased, i.e., offset by some constant amount or factor. However, even if the utmost care is taken in setting the instrument to zero, one can only say that it has been zeroed to within some value. This value may be small, but it sets a limit on the degree of certainty in the measurements and thus to the conclusions that can be drawn.
An important point to be clear about is that a systematic error implies that all measurements in a set of data taken with the same instrument are shifted in the same direction by the same amount - in unison. This is in sharp contrast to random errors where each individual measurement fluctuates independently of the others. Systematic errors, therefore, are usually most important when groups of data points taken under the same conditions are being considered. Unfortunately, there is no consistent method by which systematic errors may be treated or analyzed. Each experiment must generally be considered individually and it is often very difficult just to identify the possible sources let alone estimate the magnitude of the error. Our discussion in the remainder of this chapter, therefore, will not be concerned with this topic.