In this study, a multivariate statistical framework is applied to evaluate water quality across multiple source types in Kano State, Nigeria. We evaluated a total of 33 water samples collected from 11 locations, encompassing drinking water, groundwater, industrial wastewater, and surface water. Six physicochemical parameters in the form of pH, electrical conductivity (EC), dissolved oxygen (DO), total dissolved solids (TDS), turbidity, and total suspended solids (TSS) were analysed. Descriptive statistics, one-way analysis of variance (ANOVA), correlation analysis, principal component analysis (PCA), k-means clustering, and water quality index (WQI) assessment were employed to characterize spatial variability and pollution patterns. The results indicate pronounced differences in water quality among source types, with surface water showing the highest overall quality (mean WQI = 88.4) and industrial wastewater the lowest (mean WQI = 56.6). Compliance with drinking water standards was highest for TDS (90.9%) and lowest for turbidity (39.4%). Cluster analysis identified four water quality groups, with industrial wastewater samples predominantly forming isolated clusters, reflecting elevated pollution levels. Significant moderate correlations were observed between EC and DO (r = −0.66, p < 0.001) and between TDS and TSS (r = 0.52, p = 0.002), suggesting inter-parameter dependencies. These findings highlight the urgent need for improved industrial wastewater treatment and strengthened monitoring of groundwater resources to safeguard public health and water sustainability in the region.