When running hypothesis evaluations, it's vital to understand the potential for error. Specifically, we need to grapple with several key types: Type 1 and Type 2. A Type 1 error, also called a "false positive," occurs when you falsely reject a true null hypothesis – essentially, suggesting there's an effect when there isn't really one. Alternativ