Quality control of radar reflectivity data is essential for accurate precipitation forecasts and products of algorithms that require clean data. Radar data is frequently contaminated with non-precipitation echoes. Quality control methods should be able to remove a majority of these non-precipitation echoes as well as retain all of the actual precipitation. In this validation study, three quality control methods are tested on sixteen independent radar cases. These cases included non-precipitation such as anomalous propagation, biological returns, and electronic interference as well as actual precipitation including weak and strong convection and stratiform rain events. The data was analyzed and then hand-truthed to remove the contamination and create what we refer to as the target. The data was then run through the quality control methods and the results from each were scored against the target. Skill scores were calculated to determine which methods excel in the situations that were chosen.