What are the implications of a type I error?

A type I error occurs when a researcher incorrectly rejects a true null hypothesis, which leads to a false positive conclusion. This means that the researcher believes they have found a statistically significant effect or relationship when, in fact, there is none. The implications of a type I error can be significant, particularly in healthcare research, where it may lead to the adoption of ineffective treatments or interventions based on erroneous findings.

For instance, if a clinical trial concludes that a new medication is effective when it is not, patients may be exposed to unnecessary risks without any real benefit, ultimately affecting patient safety and care quality. The prevalence of such errors is often quantified by the significance level, typically set at 0.05, which indicates the maximum probability of making a type I error that a researcher is willing to accept. Understanding the consequences of type I errors is crucial in interpreting research results and ensuring safe medical practices.