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Comparative clustering and visualization of socioeconomic and health indicators: A case of Kenya

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  • Korir, Evans Kiptoo

Abstract

In this study, we used principal component analysis (PCA) to reduce the dimensionality of the data and used a hierarchical and K-means clustering technique to stratify counties in Kenya into five clusters. The grouped counties were then projected onto a geographic map to understand the relationship between their location and socioeconomic and health indicators. The results obtained may be useful to the county and state governments in future plans to promote inclusive and sustainable economic development.

Suggested Citation

  • Korir, Evans Kiptoo, 2024. "Comparative clustering and visualization of socioeconomic and health indicators: A case of Kenya," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    • Handle: RePEc:eee:soceps:v:95:y:2024:i:c:s0038012124001605
    DOI: 10.1016/j.seps.2024.101961
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