coefficient bias
[/ˌkoʊ.əˈfɪʃ.ənt ˈbaɪ.əs/]
nounpl: coefficient biases
viés de coeficiente
1. In statistics and machine learning, a systematic error or deviation in the estimation of regression coefficients or model parameters, often resulting from violations of model assumptions such as omitted variables, measurement error, or endogeneity.
The study found a significant coefficient bias when key variables were omitted from the regression model.
O estudo encontrou um viés de coeficiente significativo quando variáveis-chave foram omitidas do modelo de regressão.
2. A distortion in the true relationship between variables caused by the systematic nature of the estimation method or data collection process.
Coefficient bias can lead to incorrect policy recommendations if not properly identified and corrected.
O viés de coeficiente pode levar a recomendações de política incorretas se não for adequadamente identificado e corrigido.
Coefficient bias is primarily a technical term used in academic, statistical, and econometric contexts in both Brazil and the USA. It is particularly important in research, data science, and policy analysis where precise estimation is critical. The term is rarely used in casual conversation and is predominantly found in scientific papers, textbooks, and professional statistical software documentation. In Brazil, it is commonly discussed in graduate-level economics and statistics programs.
Related Idioms & Phrases
omitted variable bias leads to coefficient bias
correct for coefficient bias
identify coefficient bias in the model
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