Six Sigma Black Belt Certified Practice Exam 2025 – The All-in-One Guide to Master Your Certification!

The term used to describe the risk of a type I error in a hypothesis test is the level of significance. The level of significance is denoted by alpha (α) and represents the probability of rejecting the null hypothesis when it is, in fact, true. In other words, it quantifies the likelihood of making a type I error, which occurs when a true null hypothesis is incorrectly rejected.

A common practice in hypothesis testing is to set the level of significance at a certain threshold, such as 0.05. This means there is a 5% risk of committing a type I error. Understanding the level of significance is crucial for researchers when designing experiments and interpreting results, as it directly impacts the conclusions drawn from statistical analyses.

In the context of hypothesis testing, "power" refers to the probability of correctly rejecting a false null hypothesis, which is related to type II errors instead. The "confidence level" complements the level of significance, as a higher confidence level corresponds to a lower level of significance; this concept does not directly describe the type I error risk. "Beta risk" is associated with type II error, which occurs when a false null hypothesis is not rejected. Hence, the correct answer is clearly linked to the concept of type I