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Justyna Jupowicz-Kozak

CEO of Professional Science Editing for Scientists @ prosciediting.com

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potential bias

Grammar usage guide and real-world examples

USAGE SUMMARY

"potential bias" is a correct and usable phrase in written English.
You can use it when discussing the possibility of bias, prejudice, or partiality in any situation. For example, "The survey results may be skewed due to potential bias in the sample."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

59 human-written examples

The revelation fuelled accusations of potential bias at the social network, which has become the world's largest distributor of news.

Brits seemed keen to take the test, which shows that potential bias is something we have in mind.

News & Media

The Guardian

Quantification of potential bias.

This potential bias is apparently limited.

Validity of endpoints Classification of potential bias Quantification of potential bias (blinding, ITT, reporting).

Quality of studies (internal validity) Classification of potential bias.

We account for this potential bias through individual fixed effects.

Two sources of potential bias must be acknowledged here.

In addition, propensity scores were used to explain potential bias.

This speeds up news consumption and potential bias that may come from long-form and opinion pieces.

News & Media

TechCrunch

The Heckman selection model also allows us to control for potential bias.

Show more...

Expert writing Tips

Best practice

When discussing research, clearly state how you addressed or mitigated any "potential bias" to maintain transparency and credibility.

Common error

Don't assume that your analysis is free from "potential bias". Acknowledge and address possible biases to strengthen your argument.

Antonio Rotolo, PhD - Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Antonio Rotolo, PhD

Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Source & Trust

81%

Authority and reliability

4.6/5

Expert rating

Real-world application tested

Linguistic Context

The phrase "potential bias" functions primarily as a noun phrase, often used as a subject or object in a sentence. It signifies the possibility or existence of bias. Ludwig AI confirms this with examples demonstrating its role in various contexts.

Expression frequency: Very common

Frequent in

Science

67%

News & Media

27%

Formal & Business

6%

Less common in

Reference

0%

Wiki

0%

Encyclopedias

0%

Ludwig's WRAP-UP

The phrase "potential bias" is a common and grammatically correct noun phrase used to describe the possibility of bias in various contexts. As Ludwig AI confirms, it's prevalent in academic, scientific, and news-related content. To ensure transparency and credibility, acknowledge and address "potential bias" in your research or analysis, while also avoiding assumptions of complete objectivity. Alternatives such as "possible bias" or "risk of bias" can be used depending on the specific nuance you wish to convey.

FAQs

How can I identify "potential bias" in a research study?

Look for factors such as selection criteria, data collection methods, and funding sources that might introduce systematic errors or skewed perspectives. Consider whether the researchers acknowledge and address these "possible bias".

What's the difference between "potential bias" and actual bias?

"Potential bias" refers to the possibility of bias existing, while actual bias is confirmed presence and impact of skewed results, and influence of a systematic error. Addressing "potential bias" is crucial in maintaining the integrity of research and analysis.

How do you mitigate "potential bias" in data analysis?

Employ techniques like blinding, randomization, and statistical adjustments to minimize the impact of confounding variables. Thoroughly document your methods to ensure transparency and allow for scrutiny of any "likelihood of bias".

What are some common sources of "potential bias" in surveys?

Sources include leading questions, sampling bias (non-representative samples), and response bias (participants providing inaccurate or socially desirable answers). Careful questionnaire design and appropriate sampling techniques are essential to reduce "risk of bias".

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Source & Trust

81%

Authority and reliability

4.6/5

Expert rating

Real-world application tested

Most frequent sentences: