Stratifying: meaning, definitions and examples
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stratifying
[ ˈstrætɪfaɪɪŋ ]
data analysis
Stratifying refers to the process of dividing a population or dataset into subgroups or strata based on certain characteristics or criteria. This method is often used in statistical analysis to ensure that each subgroup is adequately represented in the sample. It allows for more precise estimates and a better understanding of the data, as variations within each stratum can be analyzed separately. Stratifying can also enhance the validity of research findings by controlling for potential confounding variables.
Synonyms
classifying, layering, segmenting.
Examples of usage
- Stratifying the sample helped to reflect different income levels.
- The researchers are stratifying the data by age and gender.
- Stratifying ensures that all demographics are considered.
Translations
Translations of the word "stratifying" in other languages:
🇵🇹 estratificando
🇮🇳 स्तरीकरण करना
🇩🇪 schichtend
🇮🇩 mengelompokkan
🇺🇦 стратифікація
🇵🇱 stratyfikacja
🇯🇵 階層化する
🇫🇷 stratification
🇪🇸 estratificación
🇹🇷 tabakalandırma
🇰🇷 계층화
🇸🇦 ت stratifying
🇨🇿 stratifikace
🇸🇰 stratifikácia
🇨🇳 分层
🇸🇮 stratifikacija
🇮🇸 lögun
🇰🇿 стратификация
🇬🇪 შენახვა
🇦🇿 sıralama
🇲🇽 estratificación
Etymology
The term 'stratify' comes from the Latin word 'stratum', meaning 'layer'. It evolved in the late 19th century as statistical methods began to develop, particularly in the context of social sciences and epidemiology. Originally used to describe geological layers, the concept was adapted to describe the classification of data into layers or strata. This concept gained prominence in the 20th century with the rise of sampling techniques and the increasing importance of objective statistical analysis in research. As researchers sought to improve the accuracy and validity of their findings, stratification became a fundamental methodology in experimental design and survey research. Today, stratifying is a common practice in various fields, including marketing, medicine, and sociology, providing deeper insights into complex datasets.