Main Article Content
Abstract
This article aims to discuss some aspects in conducting inferential analysis of census data.
In this analysis, the assumptions of normality and IID (independently and identically distribution)
in the observations are no longer realistic. Hence conventional analyses which are
based on these assumptions are invalid and unreliable. Other alternatives can be considered,
such as semivariogram analysis. Semivariogram analysis assumes that observations
are dependent geographically. The analysis is useful in understanding spatial distribution of
characteristics under investigation.
Keywords: census, aggregation, semivariogram, autocorrelation, spatial distribution
In this analysis, the assumptions of normality and IID (independently and identically distribution)
in the observations are no longer realistic. Hence conventional analyses which are
based on these assumptions are invalid and unreliable. Other alternatives can be considered,
such as semivariogram analysis. Semivariogram analysis assumes that observations
are dependent geographically. The analysis is useful in understanding spatial distribution of
characteristics under investigation.
Keywords: census, aggregation, semivariogram, autocorrelation, spatial distribution
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Economic Journal of Emerging Markets by Center for Economic Studies, Universitas Islam Indonesia is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
How to Cite
Pawitan, G. (2011). Spatial Distribution Based on Semivariogram Model. Economic Journal of Emerging Markets, 1(1), 27–35. https://doi.org/10.20885/ejem.v1i1.2282