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Difference Between Systematic Error and Random Error
In scientific research, errors can occur during the measurement of data that can affect the accuracy and reliability of the results. These errors can be classified into two categories: systematic error and random error. While both types of errors can affect the accuracy of research findings, they differ in terms of their nature, causes, and consequences. This essay aims to provide a detailed explanation of the difference between systematic error and random error.
What is Systematic Error?
Systematic errors are caused by flaws in the measurement process that consistently bias the results in a particular direction. These errors are often the result of faults in the instruments used or the methodology employed in data collection.
For instance, if a measurement instrument is not calibrated correctly, it may consistently report values that are either higher or lower than the actual values. Similarly, if a researcher does not follow the correct procedure for collecting data, the results may be skewed in a particular direction.
Systematic errors are often difficult to identify and correct, and they can significantly affect the accuracy and reliability of research findings.
What is Random Error?
Random errors are caused by chance variations in the measurement process that lead to deviations from the true value. These errors can occur due to a variety of factors, such as variations in environmental conditions, differences in the skills and experience of the person conducting the measurement, or simple human error.
Random errors are often described as 'noise' in the data and can be reduced by increasing the sample size or by conducting multiple measurements of the same variable.
Differences: Systematic and Random Error
The consequences of systematic and random errors are different. Systematic errors can lead to biased results that consistently overestimate or underestimate the true value of the variable being measured. This can result in false conclusions and inaccurate predictions.
On the other hand, random errors may not necessarily bias the results in any particular direction but can lead to imprecise and unreliable data. While random errors can be reduced by increasing the sample size or by conducting multiple measurements, systematic errors require careful identification and correction to improve the accuracy of the results.
The following table highlights the major differences between Systematic Errors and Random Errors −
Characteristics |
Systematic Error |
Random Error |
|---|---|---|
Meaning |
Systematic error, as the name implies, is a consistent, repeatable error that deviates from the true value of measurement by a fixed amount. Systematic error is the one that occurs in the same direction each time due to the fault of the measuring device. |
Any type of error that is inconsistent and does not repeat in the same magnitude or direction except by chance is considered to be a random error. Random errors are sometimes called statistical errors. |
Nature |
Systematic errors, on the other hand, can be discovered experimentally by comparing a given result with a measurement of the same quantity performed using a different method or by using a more accurate measuring instrument. Systematic errors give results that are either consistently above the true value or consistently below the true value. |
Random errors are discovered by performing measurements of the same quantity number of times under the same conditions and they involve the variability inherent in the natural world and in making any measurement. |
Cause |
Systematic errors are consistent and are caused by some flaw in the experimental apparatus or a flawed experimental design. Such errors are caused by faulty measuring devices that are either used incorrectly by individuals while taking the measurement or instruments that are imperfectly calibrated. Systematic errors are believed to be more dangerous than random errors. |
Random errors, on the other hand, are caused by unpredictable variations in the readings of a measurement device or by an observer’s inability to interpret the instrumental reading. |
Elimination |
Systematic errors can be eliminated by using proper technique, calibrating equipment and employing standards. Systematic errors are usually produced by faulty human interpretations or changes in environment during the experiments, which are difficult to eliminate completely. Repeated measurements with the same instrument neither reveal nor do they eliminate a systematic error. |
In principal, all systematic errors can be eliminated, but there will always remain some random errors in any measurement. Random errors, however, can be reduced by taking average of a large number of observations. |
Conclusion
In conclusion, systematic and random errors are two types of errors that can occur during the measurement of data in scientific research.
Systematic errors are caused by flaws in the measurement process that consistently bias the results in a particular direction, while random errors are caused by chance variations in the measurement process that lead to deviations from the true value. The consequences of these errors are also different, with systematic errors leading to biased results and random errors leading to imprecise data.
It is important for researchers to understand the nature and causes of these errors to improve the accuracy and reliability of their research findings.
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