What Is the Difference Between Systematic and Random Errors?

Systematic error refers to a series of errors in accuracy that come from the same direction in an experiment, while random errors are attributed to random and unpredictable variations in an experiment.

In physics, systematic error and random error account for all experimental errors and uncertainties. Systematic errors often arise from a problem that continues throughout the course of the experiment, while random errors are errors that arise in opposite directions and without a consistent pattern as the experiment continues. Neither type of error stems from human mistakes, which include doing calculations incorrectly or taking improper readings from instruments.

Random Errors An example of the difference between systematic errors and random errors is a simple measurement of weighing a ring three times. If a random error occurs, the person weighing the rings may get different readings of 17.2 ounces, 17.4 ounces and 17.6 ounces. Differences in these values based on random errors would be explained by limitations in the equipment used to take those measurements. While people may not be able to control or eliminate the underlying source of random error, they can reduce the rate of random error by taking larger sample sizes. Doing so helps researchers find an average over a larger group, which produces a more accurate reading. An example of a statistical error is incorrectly measuring the same object repeatedly with a faulty technique. A scientist, for instance, might take a measurement of a tomato using a string that is years old and has been stretched out from use. Therefore, the string will consistently produce inaccurate readings and results.

Systematic Errors While scientists may be able to pinpoint the source of error with an error, it can be more difficult to identify the cause of a systematic error. Systematic errors can be difficult to detect, and it can be hard for scientists to determine the extent to which a systematic error created problems. This is because the measurements collected throughout an experiment will either be consistently high or consistently low. A systematic error can be reproduced in an experiment, while a random error cannot. While a systematic error can be difficult to identify, a scientist will be able to get more accurate experimental results once he or she finds and fixes the systematic error.

Sources of Error As with random errors, systematic errors commonly occur as a result of a machine or equipment problem. Instruments with a linear response can produce two types of errors. In the first type of error, which is called zero setting or offset error, the instrument does not actually read zero, even when it is marked at zero. The second type of error is a scale factor or multiplier error. In this type of error, the instrument reads changes in the quantity to be measured as more minor or significant than the changes actually are. These types of systematic errors occur through the improper techniques of the scientist or when there is an error with the instrument itself. An example of a systematic error is a person taking inaccurate readings of solar radiation when buildings or trees cast a shadow over the area where the person is taking the measurement. Systematic errors reduce accuracy, which tells the scientist how close the instrument measurements are to the actual value.