What does a Type 1 error indicate in hypothesis testing?

In hypothesis testing, a Type 1 error occurs when the null hypothesis is incorrectly rejected. This means that the test concludes there is an effect or difference when, in reality, there is none; the null hypothesis is true. This type of error is also referred to as a "false positive."

The significance level (alpha) set for a hypothesis test helps to control the probability of committing a Type 1 error. For instance, if the alpha level is set at 0.05, there is a 5% chance of making a Type 1 error, meaning that 5% of the time, we would incorrectly reject a true null hypothesis. Understanding this concept is crucial in both research and industrial hygiene, as it could lead to incorrect conclusions about exposure risks or the effectiveness of control measures.