Unbiasedness: meaning, definitions and examples
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unbiasedness
[ ʌnˈbaɪəstnəs ]
in statistics
The quality or state of being unbiased, impartial, or fair, especially in the context of statistical analysis.
Synonyms
fairness, impartiality, neutrality.
Which Synonym Should You Choose?
Word | Description / Examples |
---|---|
unbiasedness |
Unbiasedness emphasizes a complete lack of bias. It is often used in contexts where objectivity is crucial, such as in scientific research, journalism, and statistics.
|
impartiality |
Impartiality focuses on remaining neutral and not taking sides. It is often used in legal settings, conflict resolution, and situations where judgments need to be made without favoritism.
|
fairness |
Fairness refers to treating people and situations justly and equitably. It is common in contexts involving rules, laws, and social conduct.
|
neutrality |
Neutrality is about not supporting any side in a conflict or debate. It is frequently used in political, diplomatic, or organizational contexts.
|
Examples of usage
- Researchers strive for unbiasedness in their study designs.
- Unbiasedness is crucial for obtaining accurate and reliable results.
- Statisticians use various techniques to ensure unbiasedness in their data analysis.
Translations
Translations of the word "unbiasedness" in other languages:
🇵🇹 imparcialidade
🇮🇳 निष्पक्षता
🇩🇪 Unvoreingenommenheit
🇮🇩 ketidakberpihakan
🇺🇦 неупередженість
🇵🇱 bezstronność
🇯🇵 公平性
🇫🇷 impartialité
🇪🇸 imparcialidad
🇹🇷 tarafsızlık
🇰🇷 편견 없음
🇸🇦 عدم الانحياز
🇨🇿 nestrannost
🇸🇰 nestrannosť
🇨🇳 公正性
🇸🇮 nepristranskost
🇮🇸 hlutleysi
🇰🇿 бейтараптылық
🇬🇪 მიუკერძოებლობა
🇦🇿 qərəzsizlik
🇲🇽 imparcialidad
Etymology
The term 'unbiasedness' originates from the word 'unbiased,' which dates back to the mid-17th century. The prefix 'un-' signifies the negation or absence of bias, which is the tendency to favor one thing over another. The concept of unbiasedness is fundamental in various fields, including statistics, research, and decision-making processes. It emphasizes the importance of neutrality, fairness, and objectivity in analyzing data and drawing conclusions. Achieving unbiasedness requires conscious effort, attention to detail, and adherence to rigorous methodologies.
See also: biasedly.