Data for Differentiation of nephelium lappaceum producers in Honduras: perspectives for the inclusive rural bioeconomy

The Data methodology applied multivariate statistical techniques to primary data collected from 314 producers. Principal Component Analysis (PCA) was used to reduce dimensionality, followed by K-means clustering to define the typologies. Kruskal-Wallis tests were applied to validate the significant socioeconomic and organizational differences among the identified clusters.本数据集所采用的研究方法针对从314位生产者处收集的一手数据，运用了多变量统计技术。首先通过主成分分析（Principal Component Analysis，PCA）完成维度缩减，随后结合K-means聚类算法对样本进行类型划分；进而采用Kruskal-Wallis检验，以验证所识别出的各聚类簇间存在显著的社会经济与组织层面差异。