Systematic error is a consistent repeatable error associated with faulty equipment or a flawed experiment design. These errors are usually caused by measuring instruments that are incorrectly calibrated or are used incorrectly. However, they can creep into your experiment from many sources, including:
A worn out instrument. For example, a plastic tape measure becomes slightly stretched over the years, resulting in measurements that are slightly too high.
An incorrectly calibrated or tared instrument, like a scale that doesn’t read zero when nothing is on it.
A person consistently takes an incorrect measurement. For example, they might think the 0.25 m mark on a ruler is the 0.2 m mark.
Systematic errors produce consistent errors, either by a fixed amount (like 1 g) or a percentage (like 105% of the true value). If you repeat the experiment, you will get the same error.
How to identify systematic error
Systematic errors affect the accuracy of measurements. Low accuracy indicates the presence of systematic error(s).
It’s difficult to detect - and therefore prevent - systematic error. In order to avoid these types of error, know the limitations of your equipment and understand how the experiment works. They can often be identified by repeating the experiment using different equipment (this will highlight any issues with calibration or worn equipment but will not fix errors in measuring technique). These errors are generally overcome by recalibrating the equipment with known standards or, if the cause of the error is known, adjusting the measurements by the required amount.
To identify systematic error using the graph, look for:
zero offset error - The graph does not pass through the origin when it is theoretically expected to.
multiplier or scale factor error – The calculated slope does not match the expected slope. This error may also show up as a difference between an accepted value and a value derived using the calculated slope.
Note: an offset only indicates a systematic error if the line of best fit was expected to pass through the origin.
Error and percentage error
To comment on accuracy and the impact of systematic errors on an experiment, we can use the error or percentage error of the measurements.
error = measured value - actual value
Practice
Check that you know the difference between random and systematic errors.