What does a Type 1 error indicate in hypothesis testing?

What does a Type 1 error indicate in hypothesis testing?

• A. Fail to reject the null when it is false
• B. Reject the null when it is true
• C. Fail to reject the null when it is true
• D. Reject the alternative hypothesis correctly

Answer: (B)

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.

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.