Which error can result in a researcher concluding that a treatment has effects when it actually does not?

A Type I error occurs when a researcher incorrectly rejects the null hypothesis when it is true. In the context of a treatment effect, this means that the researcher concludes that the treatment has a significant effect on the outcome, even though, in reality, it does not. This can happen due to random chance or variability in the data, leading to the misconception that the treatment is effective when it is actually not.

Type I errors are particularly problematic in research because they can lead to the development of ineffective treatments or interventions, wasting resources and potentially harming participants. Researchers strive to control the probability of making a Type I error, often by setting a significance level (e.g., p < 0.05) to minimize the likelihood of incorrectly declaring a treatment effect. Understanding this concept is crucial for interpreting research findings accurately and maintaining the integrity of scientific inquiry.