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Aggregate data are applied in statistics, data warehouses, and in economics. There is a distinction between aggregate data and individual data. Aggregate data refers to individual data that are averaged by geographic area, by year, by service agency, or by other means. [ 2 ]
Data aggregation is the compiling of information from databases with intent to prepare combined datasets for data processing. [1] Description
The aggregation problem is the difficult problem of finding a valid way to treat an empirical or theoretical aggregate as if it reacted like a less-aggregated measure, say, about behavior of an individual agent as described in general microeconomic theory [1] (see representative agent and heterogeneity in economics). The second meaning of ...
Economic data are data describing an actual economy, past or present. These are typically found in time-series form, that is, covering more than one time period (say the monthly unemployment rate for the last five years) or in cross-sectional data in one time period (say for consumption and income levels for sample households).
In input-output analysis, disaggregated data on gross and net outputs of different economic sectors and sub-sectors is used to study the transactions between them. Thus, for example, a sector purchases inputs from several other sectors and sells outputs to several other sectors.
Spatial data configuration in then statistical analysis of regional economic and related problems. Dordrecht: Kluwer Academic Publishers. This article contains quotations from Modifiable areal unit problem at the GIS Wiki, which is available under the Creative Commons Attribution 3.0 Unported (CC BY 3.0) license.
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. The data may also be collected from sensors in the environment, including traffic cameras, satellites, recording devices, etc.
Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. . The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data or produce summary data and statistics at different aggregation levels for various applications