Redundancy refers to the concept of having backup or duplicate systems, components, or resources in place in case of failure or error in a primary system. In research, redundancy can refer to the incorporation of multiple methods, approaches, or measures to ensure the reliability and validity of results. This can include replicating experiments, using multiple data sources, or employing different analytical techniques to cross-validate findings. Redundancy in research is important for reducing the risk of errors or bias and increasing the robustness of study findings.