Controlling for Type I error is crucial because of the potential consequences of false positives. These errors can lead to the implementation of ineffective or harmful interventions, misallocation of resources, and erosion of public trust in scientific findings. To mitigate these risks, researchers use various statistical techniques and adhere to rigorous study designs.
