A Type I Error occurs when a researcher incorrectly rejects a true null hypothesis. This means that the researcher concludes there is an effect or difference when, in reality, none exists. For example, in a clinical trial, a Type I Error might lead to the false belief that a new drug is effective when it is not. The probability of making a Type I Error is denoted by the Greek letter alpha (α), often set at 0.05. This means there is a 5% chance of incorrectly rejecting the null hypothesis. Minimizing Type I Errors is crucial in scientific research to ensure valid and reliable results.