Примеры использования Data editing на Английском языке и их переводы на Русский язык
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Data editing at SORS.
Work Session on data editing Nov. 95.
Data editing in the Danish CPI.
It contains components for data editing.
Data editing and summary.
Люди также переводят
Challenges(cont.) Data editing/quality control.
Data editing and/or imputation.
Census data capture and data editing.
Data editing is a costly and time-consuming process.
Work Session on data editing Oct. 94 and Oct. 96.
Data editing with direct access to the scanned questionnaires;
Remote access to site's data editing for technical personnel.
Data editing can be adapted to individual groups of operators;
K-Base provides a repository for information andresources related to data editing.
The use of data cleaning tools makes data editing process efficient.
Data editing is often a very resource-intensive activity for national statistical offices.
The question is also relevant in the context of automated data editing facilities in the field.
History: Formerly data editing group within the Statistical Computing Project SCP and SCP.2.
Recommendations on the best practices on the evaluation of the efficiency of the data editing process.
Examples of various approaches to data editing, including the use of administrative records.
The most important aspect of this new approach is the standardization of data collection and data editing operations.
It was pointed out that in designing data editing rules, there is a danger of over-editing.
Vector data editing, after automatic tracing in particular consists of numerous operations of vector line cutting and joining.
Publish methodological guides on data quality control, data editing and imputation.
Data editing is concerned with the identification and, if possible, the correction of erroneous or highly suspect survey data. .
Using administrative data to improve the data editing strategy, or the quality of the estimates;
Box 3.25: Data editing of diaries in the 2003 Italian Time Use Survey words to be interpreted in context and particular types of reporting problems to be identified.
In the second case, the correction application"KjeKorr" for the first time in Statistics Austria shifted data editing from the mainframe to the PC level.
Automated data editing algorithms, such as Tukey, will not test for this unless part of a broader package of editing procedures.
Some methods of addressing data quality issues include targeted training in survey quality assurance, applying specialized assessment frameworks, andintroducing user-friendly packages for data editing.