Error is a part of measurement. In an experiment, the aim is to get accurate result. But, practically it is very difficult to achieve 100% accuracy in a measurement. When the measured value differs from the actual value, then there is an error in that measurement. That means, if there is no 100% accuracy, then definitely there is an error. In another article, we have discussed the Accuracy and Precision in a measurement. In this article, we are going to discuss different types of errors in measurement, their sources and corrections.
Contents in this article:
- What are errors in measurement?
- Types of errors in measurement
- Sources of errors in measurement
- Corrections of errors in physics experiment
What are Errors in measurement?
Errors are the parts of measurement which can differ the measured value of a physical quantity from its actual or true value. There are several causes of error in a measurement. So, care should be taken on these causes to get the correct experimental value of a physical quantity.
Types of Errors in measurement
There are mainly three types of errors in a measurement as followings –
- Systematic error
- Random error
- Gross error or human error
The detailed explanation of these errors are given below.
Systematic Errors in measurement
The systematic error is a predictable error that is caused by imperfect instrument or observational mistakes or bad impact of environment during the measurement. This type of error can be easily eliminated after identifying its causes. In systematic error, similar kind of error occurs in every observation. Because, the same causes are equally present during every observation.
Sources of systematic error
The causes of systematic error are –
- The imperfect instrument
- Mistakes while observing the data
- Bad impact of environment
Types of systematic error
On the basis of the causes, the systematic error has three types –
- Instrumental error
- Observational error
- Environmental error
Some of the instruments do not have a perfectly zero offset. This is due to the imperfect calibration or mismatch of the components of the instrument. It is possible to achieve the zero offset by mechanical adjustments of the instrument.
There can be some errors in reading the data. This is the observational error. Observational error is also a kind of systematic error. A proper care during taking the data can eliminate the observational error.
Some of the experiments (specially, chemical experiments) depend on the environmental conditions like pressure, temperature, humidity, etc. to show a better result. Clearly, the environment can introduce errors in an experiment. These are the environmental errors.
Corrections of Systematic Error
One can correct the systematic error by
- Using an errorless instrument or adjusting the zero offset of the instrument.
- Taking proper cares while taking observations.
- Maintaining the proper environment for the experiment. If naturally is not possible, then it could be done artificially.
Random Errors in measurement
The random error is the unpredictable error that arises due to the uneven fluctuations of the variables. It is very difficult to restrict the fluctuations of the variables. Again, the fluctuation of variables becomes different for different observations. This makes difficult to eliminate this type of error.
Sources of Random error
The sources of random error in an experiment are –
- Uneven fluctuations of variables.
- Uncontrollable environmental conditions.
Corrections of Random error
As the random error is unpredictable, it is almost impossible to correct the random errors in an experiment.
Gross Error or Human Error
The Gross errors or human errors are the mistakes made by human while doing an experiment. This can widely differ the measured value from its original value. But, this type of error can be eliminated by performing the experiment with proper cares.
This is all from the article on different types of errors in measurement, their sources and corrections. If you have any doubt on this topic you can ask me in the comment section.
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