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Edit Statistical Mapping

Edit Statistical Mapping (ESM) is a statistical technique used mainly in data validation, error detection, and imputation. It’s often applied in official statistics and large surveys. The method works by:
Defining a set of edits (logical or mathematical rules) that data records must satisfy.
Example: Income ≥ 0, Age ≥ 15 if Employment Status = “Employed”.
Identifying inconsistencies in the data when these edits are violated.
Using statistical mapping to correct or impute missing/inconsistent values based on relationships in the dataset.
Ensuring coherence of microdata so that it aligns with macro-level aggregates.
Supporting survey data cleaning, census editing, and economic statistics preparation.
It’s particularly important for official statistics agencies because data collected from respondents often contains errors, missing entries, or contradictions. ESM ensures that the final dataset is internally consistent, reliable, and ready for analysis.
Defining a set of edits (logical or mathematical rules) that data records must satisfy.
Example: Income ≥ 0, Age ≥ 15 if Employment Status = “Employed”.
Identifying inconsistencies in the data when these edits are violated.
Using statistical mapping to correct or impute missing/inconsistent values based on relationships in the dataset.
Ensuring coherence of microdata so that it aligns with macro-level aggregates.
Supporting survey data cleaning, census editing, and economic statistics preparation.
It’s particularly important for official statistics agencies because data collected from respondents often contains errors, missing entries, or contradictions. ESM ensures that the final dataset is internally consistent, reliable, and ready for analysis.
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受保護腳本
此腳本以閉源形式發佈。 不過,您可以自由且不受任何限制地使用它 — 在此處了解更多資訊。
免責聲明
這些資訊和出版物並不意味著也不構成TradingView提供或認可的金融、投資、交易或其他類型的意見或建議。請在使用條款閱讀更多資訊。