Systematic vs Random Error: Difference and Comparison

It becomes almost impossible to avoid errors when taking the exact measurements or facing problems with the equipment. The measurements of physical quantities cannot always be the correct values.

To avoid such errors, scientists try to classify errors and remove uncertainties in their measurements.

There are two main kinds of errors- Systematic error and Random error. Knowing about systematic and random errors helps us to perform the experiments better and to reduce errors.

Key Takeaways

  1. Systematic error is a consistent, repeatable deviation from the true value in a measurement or experiment, caused by faulty equipment or biased methodology.
  2. Random error is an unpredictable, inconsistent deviation from the true value due to unpredictable factors, such as measurement techniques or environmental conditions.
  3. The key differences between systematic and random errors lie in their causes and predictability, with systematic errors being consistent and attributable to specific factors. In contrast, random errors are inconsistent and difficult to predict.

Systematic vs. Random Error

Systematic errors occur due to flaws in experimental design or equipment, such as a misaligned instrument, faulty calibration, or improper measurement method. Random errors can lead to imprecision but can be reduced by taking multiple measurements and averaging results.

Systematic vs Random error

 

Comparison Table

Parameters of ComparisonSystematic ErrorRandom Error
MeaningA systematic error is an error that arises because of a fault in the measuring device.A random error is an error that arises because of unpredictable changes in the environment.
RepetitiveSystematic errors are repetitive.Random errors are not repetitive.
CausesFlaws in the experimenting equipment.Unpredictable variations in readings and disturbances in the environment.
ReductionSystematic errors can be reduced by using the correct apparatus or proper techniques.Random errors can be reduced by repeating the readings and increasing the number of observations.
TypesThree types: Instrument, Environment, and Systematic error.No types.
ReproducibleThese are reproducible.These are not reproducible.
Magnitude of errorConstantVary

 

What is Systematic Error?

Systematic error is also known as systematic bias. These are consistent errors that can be repeated because of the flawed experimental design.

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Sources of systematic errors:

  1. Incorrectly calibrated instrument
  2. Worn out instrument
  3. An individual taking the measurement incorrectly

There are three types of systematic errors:

  1. Instrumental error- Basically, there are three causes of instrumental errors:
    1. Misuse of the experimental setup.When the mechanical structure of the setup is not perfect.
    1. When there is a loading effect.
  2. Observational error arises when the observer does not interpret the readings correctly.
  3. Environmental error- When there are changes in the surroundings, such as pressure, humidity, and so on, it may give rise to environmental errors.
 

What is Random Error?

As the name suggests, a random error is irregular and cannot be forecasted. Such errors arise when some limitations are not in the experimenter’s control.

Random error is also known as statistical error. This is so because such errors can be eliminated by statistical means because it is irregular and inconsistent.

Unlike systematic errors, random errors can be decreased by taking the observations repeatedly and the average of many observations.


Main Differences Between Systematic and Random Error

  1. Systematic errors are reproducible, whereas random errors are not reproducible.
  2. The magnitude of error is constant in systematic errors and may vary in random errors.

References
  1. https://journals.ametsoc.org/mwr/article/121/1/173/65053
  2. https://journals.ametsoc.org/jhm/article/17/4/1119/342820

Last Updated : 11 June, 2023

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27 thoughts on “Systematic vs Random Error: Difference and Comparison”

    • It’s true, the nature of random errors and the difficulty of prediction could be highlighted more strongly to avoid misconceptions.

      Reply
  1. This article is extremely informative. The discussion on the sources of systematic errors is particularly insightful.

    Reply

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