uncertain data

USAGE SUMMARY

The phrase "uncertain data" is correct and usable in written English.
It can be used when referring to information or statistics that lack reliability or clarity. Example: "The research findings were based on uncertain data, making it difficult to draw definitive conclusions."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

59 human-written examples

However, some elements may involve uncertain data in practice.

Journal of Inequalities and Applications

They studied robust DEA model under continuous uncertain data.

Journal of Industrial Engineering International

In the above model, only matrix A includes uncertain data.

Journal of Modern Power Systems and Clean Energy

First, these uncertain data are estimated by appropriate adaptive laws.

Computers & Structures

Mobile robot localization deals with uncertain sensory information as well as uncertain data association.

Robotics and Autonomous Systems

Many planning and production processes are characterized by uncertain data and uncertain information.

Structural Safety

Properties of materials often presented as uncertain data in references of materials science and selection.

Journal of Industrial Engineering International

In this context, "uncertain data" refers to spatial and component data which are not easily standardisable.

Heritage Science

Conveying uncertain data using concrete map images may also introduce communication obstacles (Severtson and Myers 2013).

Journal of Applied Volcanology

The uncertain data may be degenerated and utilized in crisp MADM models.

Journal of Industrial Engineering International

We employ various concepts of interval computations to reduce degeneration of uncertain data.

Journal of Industrial Engineering International

Expert writing Tips

Best practice

When presenting "uncertain data", clearly state the limitations and potential biases associated with it. Always use appropriate disclaimers to manage expectations and maintain transparency.

Common error

Avoid drawing definitive conclusions based solely on "uncertain data". Instead, frame your findings as tentative or preliminary, and emphasize the need for further investigation to validate the results.

Linguistic Context

The primary grammatical function of "uncertain data" is as a noun phrase, typically serving as the subject or object of a sentence. Ludwig AI indicates this phrase is used to describe information lacking precision or reliability. Examples from Ludwig show its use in various contexts, such as discussing limitations in research or challenges in modeling.

Expression frequency: Very common

Frequent in

Science

95%

Formal & Business

3%

Wiki

1%

Less common in

News & Media

0%

Reference

0%

Social Media

0%

Ludwig's WRAP-UP

In summary, "uncertain data" is a noun phrase widely employed, especially within scientific and technical domains, to denote information that lacks precision or reliability. As Ludwig AI confirms, this phrase is grammatically sound and frequently used. While its prevalence in academic and research contexts underscores a formal register, it is crucial to acknowledge and address limitations when presenting "uncertain data", ensuring transparency and avoiding overstating conclusions. Employing methods like sensitivity analysis and robust optimization can further mitigate the impact of data uncertainty on decision-making. Related phrases, such as "unreliable information" or "ambiguous data", can also be used to describe similar concepts, depending on the specific nuances you want to convey.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

unreliable information

Emphasizes the lack of dependability in the information.

ambiguous data

Highlights the unclear or multiple possible interpretations of the data.

imprecise figures

Focuses on the lack of exactness or accuracy in numerical data.

questionable statistics

Suggests doubt or skepticism about the validity of the statistical data.

approximate values

Indicates that the values are close but not necessarily exact.

estimated results

Implies that the results are based on estimation and may not be precise.

speculative findings

Highlights the tentative and conjectural nature of the findings.

debatable facts

Suggests that the "facts" are open to discussion and disagreement.

inconclusive evidence

Focuses on the lack of definitive proof provided by the evidence.

equivocal information

Emphasizes the open to interpretation aspect of the information.

FAQs

How is "uncertain data" used in scientific research?

In scientific research, "uncertain data" is often used in modeling and simulation, where parameters may not be precisely known. Statistical methods and sensitivity analyses are employed to assess the impact of this uncertainty on the results.

What are some techniques for dealing with "uncertain data"?

Common techniques include sensitivity analysis, Monte Carlo simulation, Bayesian inference, and robust optimization. These methods help to quantify and manage the impact of uncertainty on decision-making.

How does "uncertain data" affect the reliability of a study?

"Uncertain data" can reduce the reliability of a study's conclusions. It's crucial to acknowledge and address the uncertainty through appropriate statistical methods and cautious interpretation of results. Transparency in reporting limitations is key.

What's the difference between "uncertain data" and "incomplete data"?

"Uncertain data" refers to data where the value is not precisely known, but some information about its possible range or distribution is available. "Incomplete data", on the other hand, means that some data points are missing altogether.