Overprecision (overconfidence in interval estimation) is a bias with clear implications for economic outcomes in industries reliant on forecasting possible ranges for future prices and unknown states of nature, such as mineral and petroleum exploration. Prior research has shown the ranges people provide are too narrow given the knowledge they have; that is, they underestimate uncertainty and are overconfident in their knowledge. The underlying causes of this bias are, however, still unclear and individual differences research has shed little light on traits predictive of susceptibility. Taking this as a starting point, this paper directly contrasts the Naïve Sampling Model and Informativeness-Accuracy Tradeoff accounts of overprecision, seeing which better predicts performance in an interval estimation task. This was achieved by identifying traits associated with these theories – Short Term Memory and Need for Cognitive Closure, respectively. Analyses indicate that NFCC but not STM predicts interval width and thus, potentially, impacts overprecision.