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Correction Factor

Last updated: May 14, 2019

What Does Correction Factor Mean?

A correction factor is a factor multiplied with the result of an equation to correct for a known amount of systemic error.

Although many numerical evaluations are likely to be precise, you may not always arrive at a specific conclusion in terms of measurements. This is because multiple factors can come into play, resulting in skewed conclusions. Oftentimes the need for evaluating these uncertain factors is a necessity.

This process of evaluating factors that lead to uncertainty in measurement results is known as uncertainty evaluation or error analysis. Error analysis is dependent on correction factors, which are designated calculations implemented to evaluate uncertain factors in measured results.

Safeopedia Explains Correction Factor

The correction factor in a measured value retains its importance in properly evaluating and investigating the veracity of an experimental result. A view of the correction factor in an experimental result allows the evaluators of the result to analyze it, keeping in mind the impact of uncertainty factors on the results. In turn, they can utilize or reject the experimental result based on accuracy in spite of uncertainty factors.

In laboratory settings and in test studies, error analysis aided by correction factors is of prime value. To arrive at correction factors, one must follow a systematic path of evaluating uncertainty factors in measured results. This systematic path or calculation used to arrive at the best or closest value of a measured result is stated below:

measurement = (best estimate ± uncertainty) units

This allows for the depiction of a range of values of a measured result that includes the true value. While this is not technically a conclusive analysis, it is definitively the best and most-complete analysis of a measured result.

In error analysis or uncertainty evaluation, much is to be said of factors such as precision and accuracy when arriving at the true value of a measured result. Both these factors should be accounted for by the uncertainty estimate. Clear definitions of precision and accuracy as applied to error analysis are detailed below:

  • Accuracy is defined by the closeness between a true or accepted value and a measured value. Inaccuracy in this case pertains to the measurement error margin in the measured value.
  • Precision takes into consideration the well-defined nature of a measured value without considering theoretical value. Precision accounts for factors such as consistency and agreement among independent measurements of the same quantity, as well as the reliability or reproducibility of the result.

In Pugh & Winslow's (1966) "The Analysis Of Physical Measurements," precision is related to the random error distribution associated with a particular experiment or even with a particular type of experiment. Accuracy is related to the existence of systematic errors—differences between laboratories, for instance. As an example, one could perform very precise but inaccurate timing with a high-quality pendulum clock that had the pendulum set not quite at the right length.

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