Sampling density is an important parameter in different stages of exploration programs such as stream sediment-based geochemical exploration. Some researchers have suggested the effects of different sampling densities in regional exploration. However, a few researchers have addressed the effect of stream sediment sampling density on anomaly delineation. This research aims at investigating the effect of sampling density in delineating ore-related geochemical signals in stream sediment exploration through sensitivity analysis. A dataset from northwestern Iran with known copper occurrences was employed, and the available data was systematically resampled into different proportions to simulate different sampling densities and analyzed using the true sample catchment basin approach. The results showed a positive correlation between the number of outlining known deposits and sampling density, implying that a higher sampling density increases the chance of outlining new potential zones. Moreover, when sampling density increases, the total size of the delimited anomalous area decreases. The estimated background values (Mj) for upstream lithologic units varies heavily with sampling density. This is critical as separating anomalous basins depends on Mj. Mj variation has been more emphasized for lithologies with high estimated background content, displaying heteroscedastic behavior.