Orthogonal arrays are structured arrangements used in statistics and experimental design to systematically explore the effects of multiple factors. They help in organizing experiments so that the interactions between different variables can be analyzed efficiently. Each combination of factors is tested in a way that minimizes bias and maximizes the information gained from the results. These arrays are particularly useful in fields like quality control, computer science, and bioinformatics. By ensuring that each level of a factor is tested equally across all other factors, orthogonal arrays facilitate a balanced comparison, leading to more reliable conclusions about the relationships between variables.