truthfulness of data

USAGE SUMMARY

The phrase "truthfulness of data" is correct and usable in written English.
It can be used when discussing the accuracy, reliability, or integrity of data in various contexts, such as research, data analysis, or reporting. Example: "The truthfulness of data is crucial for making informed decisions in our research study."

✓ Grammatically correct

Science

News & Media

Encyclopedias

Human-verified examples from authoritative sources

Exact Expressions

2 human-written examples

The non-perturbative techniques preserve the truthfulness of data.

BMC Medical Informatics and Decision Making

However, when dealing with health data, non-perturbative methods are favoured because they preserve the truthfulness of data [ 87].

BMC Medical Informatics and Decision Making

Human-verified similar examples from authoritative sources

Similar Expressions

58 human-written examples

In addition there is veracity, which refers to the accuracy and truthfulness of the captured data and the meaningfulness of the results generated from the data for certain problems.

Journal of Internet Services and Applications

Our data was limited by the fact data on reported risk factors depended on the memories of study participants, and there was no other means to verify the truthfulness of this information.

BMC Pregnancy and Childbirth

The perturbative methods distort the truthfulness of the records in a data set.

BMC Medical Informatics and Decision Making

It is about giving voters more information to evaluate the truthfulness of an ad's claims.

The New York Times

We analytically prove the truthfulness of the proposed online auction scheme without requiring any information about bidders behavior.

EURASIP Journal on Wireless Communications and Networking

The truthfulness of the performances is exceptional.

The Guardian

This attitude follows from the revelation of the truthfulness of kami in man.

Encyclopedia Britannica

It has to do with determination and the rightness and the truthfulness of the ideas".

The New York Times

"Filers are responsible for the truthfulness of their filings," it explained.

The Economist

Expert writing Tips

Best practice

When evaluating research or reports, always question the "truthfulness of data" to ensure findings are based on sound evidence.

Common error

Don't assume data is truthful without verification. Always cross-reference data with other sources or methodologies to ensure accuracy.

Linguistic Context

The phrase "truthfulness of data" functions as a noun phrase, typically acting as the subject or object of a sentence. It describes a quality or attribute of data, emphasizing its accuracy and reliability. As shown by Ludwig, this phrase is often used in contexts where the integrity of information is critical.

Expression frequency: Common

Frequent in

Science

50%

News & Media

30%

Encyclopedias

20%

Less common in

Formal & Business

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

The phrase "truthfulness of data" is a noun phrase used to describe the accuracy and reliability of information. Ludwig AI states that it's grammatically correct and usable in written English, highlighting its importance in various contexts such as research, data analysis, and reporting. It is most frequently found in scientific and news-related contexts. When using this phrase, remember to emphasize the need for verification and cross-referencing to avoid making decisions based on flawed data. Alternatives such as "data accuracy" and "data reliability" can be used to convey similar meanings.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

data accuracy

Focuses specifically on the correctness of the data.

data reliability

Emphasizes the consistency and dependability of the data.

data validity

Highlights whether the data measures what it is supposed to measure.

data integrity

Refers to the completeness and consistency of the data.

accuracy of information

Broader term that applies to information in general, not just data.

reliability of information

Focuses on the dependability of the information.

veracity of data

Emphasizes the truthfulness and honesty of the data.

authenticity of data

Indicates whether the data is genuine and not forged.

data precision

Highlights the level of detail and exactness in the data.

data correctness

Directly addresses whether the data is free from errors.

FAQs

How can I assess the "truthfulness of data" in a research paper?

You can assess the "truthfulness of data" by examining the methodology, sample size, and sources used. Look for potential biases or limitations that could affect the "data accuracy".

What's the difference between "truthfulness of data" and "data reliability"?

"Truthfulness of data" refers to whether the data is factual and accurate, while "data reliability" refers to the consistency and dependability of the data over time and across different contexts.

Why is the "truthfulness of data" important in decision-making?

The "truthfulness of data" is crucial because decisions based on inaccurate or false data can lead to negative consequences, such as incorrect strategic choices or flawed policies.

What are some strategies to improve the "truthfulness of data" collection?

Strategies to improve the "truthfulness of data" include using validated instruments, employing rigorous quality control measures, ensuring anonymity and confidentiality to reduce response bias, and triangulating data from multiple sources.