The Application of Clustering as a Statistical Analysis Method in Assessing The Socio-Economic Development of Regions

The application of the clustering statistical analysis method in assessing the socio-economic development of regions has gained significant relevance amidst global economic instability and disparities in resource distribution. This study examines the clustering of cities and districts in the Khorezm region of the Republic of Uzbekistan based on socio-economic development indicators from 2017 to 2024. The clustering of cities and districts was conducted using the "Cluster Analysis" method. According to the research findings, the cities and districts of the Khorezm region were divided into five clusters. This clustering was performed based on the "Euclidean distance" measure. The Euclidean distances reflect the degree of similarity, where a larger distance indicates a lower level of similarity, and a smaller distance signifies a higher level of similarity. Elements identified as the most similar were grouped into the same cluster.