measurement of error

USAGE SUMMARY

The phrase "measurement of error" is correct and usable in written English.
It can be used in contexts related to statistics, data analysis, or quality control when discussing the quantification of inaccuracies in measurements or predictions. Example: "The measurement of error in our data set revealed significant discrepancies that needed to be addressed."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

2 human-written examples

Much work currently has been focused on the measurement of error motions and spindle balancing.

International Journal of Machine Tools and Manufacture

There is a term in the measurement of error that scales as one over the square root of the sample size ( <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0003179.e001.PNG" class= inline-graphic"/> ).

Plosone

Human-verified similar examples from authoritative sources

Similar Expressions

58 human-written examples

This paper introduces the concept of distribution distance for the measurement of errors in exact and approximate methods for stochastic simulation of chemically reacting systems.

Journal of Computational Physics

These data also facilitate the assessment and measurement of errors of omission, i.e., the lack of use of appropriate drugs when needed.

European Journal of Clinical Pharmacology

To characterize the misclassification process, we consider a practical situation where replicated measurements of error-prone covariates are available.

Journal of Statistical Distributions and Applications

In Section 4, we develop inferential procedures to accommodate misclassification effects with the availability of replicated measurements of error-contaminated covariates.

Journal of Statistical Distributions and Applications

Our development is carried out under a practical setting where a validation sample is impossible but repeated measurements of error-contaminated variables are available.

Journal of Statistical Distributions and Applications

Eligible participants underwent a complete ophthalmologic examination including a non-dilated measurement of refractive error (Table  1) of both eyes.

Human Genetics

By this approach, the statistical errors are reduced which enables a very precise measurement of systematic errors between both setups.

Biomedical Optics Express

The assumption of the same distribution of measurement error of the c levels of the controls.

Plosone

The present results will assist in establishing a method for the reliable measurement of refractive errors in individuals.

BMC Ophthalmology

Expert writing Tips

Best practice

When reporting the "measurement of error", always specify the units of measurement (e.g., percentage, standard deviation) to provide a clear understanding of the error's magnitude.

Common error

Avoid using "measurement of error" interchangeably with precision. Accuracy refers to how close a measurement is to the true value, while precision refers to the repeatability of the measurement. The "measurement of error" relates directly to accuracy, not necessarily precision.

Linguistic Context

The phrase "measurement of error" functions primarily as a noun phrase that identifies the process of quantifying the inaccuracy present in a measurement. Ludwig AI confirms the phrase's correctness and usability in English.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

0%

Ludwig's WRAP-UP

The phrase "measurement of error" is a grammatically sound and commonly used term, particularly within scientific contexts. As Ludwig AI indicates, it effectively quantifies inaccuracies in measurements. The most suitable alternatives are "error quantification" and "error assessment". When using this phrase, it is crucial to specify the units of measurement. A common pitfall is confusing accuracy with precision; remember that the "measurement of error" primarily addresses accuracy. This phrase helps to evaluate data reliability, identify biases, and inform better decisions. It is mainly used in formal contexts.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

error quantification

Focuses on the act of quantifying the error, simplifying the phrase.

quantifying errors

Rephrases the phrase as a gerund, emphasizing the action of quantifying.

error assessment

Emphasizes the evaluation or judgment of error magnitude.

calculating error

Focuses on the mathematical process of finding the error value.

determination of error

Focuses on the act of finding or establishing the error.

magnitude of error

Highlights the size or extent of the error.

quantification of uncertainty

Broadens the scope to include all types of uncertainty, not just error.

assessment of inaccuracies

Replaces "error" with "inaccuracies", highlighting the lack of precision.

error analysis

Highlights the detailed examination of errors to understand their nature and causes.

evaluation of deviations

Uses "deviations" to refer to errors, focusing on the difference from an expected value.

FAQs

How do you use "measurement of error" in a sentence?

You can use "measurement of error" to describe the process of quantifying inaccuracies. For example, "The "measurement of error" in the experiment was crucial for validating the results."

What is another way to say "measurement of error"?

Alternatives to "measurement of error" include "error quantification", "error assessment", or "quantification of uncertainty", depending on the specific context.

What is the importance of "measurement of error"?

The "measurement of error" is essential for evaluating the reliability and validity of data. It helps identify potential biases and limitations in research findings, informing better decision-making.

Which statistical measures are commonly used in "measurement of error"?

Common statistical measures used in the "measurement of error" include standard deviation, mean absolute error, root mean squared error, and confidence intervals. The choice of measure depends on the nature of the data and the research question.