Many different astronomical sources like pulsar wind nebulae and quasars emit gamma rays, which collide into Earth’s atmosphere and produce gamma-ray showers that are measured by VERITAS. Abundant cosmic rays create similar showers to gamma rays, which make it challenging to identify a gamma-ray signal. Thus, different selection criteria are used to limit influence of background cosmic ray signals. The number of target area events is then compared to the estimated number of background events to calculate the significance of a gamma-ray detection. The standard analysis applies the same selection criteria to all events, independent of energy, and this study aimed to improve upon that by testing different criteria together. Significances of gamma-ray signals were calculated for three different possible energy spectra of the source. Data from the Crab Nebula were split into training and validation samples, with multiple analyses being performed on each. The optimal data analyses in different energy ranges were combined for both training and validation samples. The results were compared with one another and confirmed the consistency of this new analysis. These results were then compared to the standard analysis. With this new analysis, improvements were found in the significance of the three different spectra in comparison to the standard analysis. The results of this study could lead to major benefits in future gamma-ray research. Sources that were previously considered insignificant with the standard analysis could now be considered significant with the new analysis, potentially allowing new sources to be discovered.