Understanding The Systematic Errors With Examples For Studies

Understanding The Systematic Errors With Examples For Studies

Systematic error is a consistent error which gets repeated due to the faulty instruments or any other kinds of errors occurring during the experiment. These errors can also occur due to the use of improper instruments while experiments.

It is also said that the error occurs due to the deviation while using the instrument or performing the experiment. These kinds of errors can be fixed by using the proper instruments which are not faulty.

It cannot be prevented by recording a large number of readings while performing the experiments. These errors can be of two types such as-

1. Offset error – This error happens when the initial value of the instrument is not taken as zero.

2. Scale factor error – This error happens in proportion to the true value. It is called a scale factor as the proportion of the error can vary according to the instrument.

Understanding The Systematic Errors With Examples For Studies

A random error is described as a kind of error that fluctuate because of unpredictability or uncertainty inherent in your measuring process or the difference in the quantity you are trying to measure. For example, a scientist measuring an insect, he would try to place the insect at the zero point of a ruler or measuring stick and read the value at the other end.

The ruler itself will probably just measure down to the nearest millimeter and reading this in this method with accuracy would be difficult. You may underestimate or overestimate the actual size of the insect according to how well you read the scale and your decision as to where the head of the insect ends. You might not even realize that the insect slightly moved from the zero position.

A systematic error, on the other hand, is a kind of error that results from a persistent issue and leads to a consistent error in your measurements. Like for example, if you are using a measuring tape and it has been stretched out, the results of your measurements will always be lower than the correct value.

Another example would be if your weighing scale has not been set to zero beforehand, there will be a systematic error resulting from the mistake in the calibration.