Which term is defined as a false rejection of the null hypothesis?

The term that describes a false rejection of the null hypothesis is known as a Type I error. In hypothesis testing, the null hypothesis is the statement that there is no effect or no difference, and a Type I error occurs when researchers conclude that there is an effect or a difference when in reality, none exists. This usually happens when the significance level, which is the probability of making a Type I error, is set, for example, at 0.05. If the p-value of the test is less than the significance level, the null hypothesis is rejected, potentially leading to a Type I error if the null hypothesis is true.

Understanding Type I errors is critical in the context of statistical hypothesis testing, as it highlights the risks of claiming findings that might not be true. This is especially significant in fields like medicine or criminal justice, where the consequences of such errors can have critical implications.