Board of Certified Safety Professionals (BCSP) Practice Exam

What is the alpha error in a symmetric uniform distribution with a 0.99 confidence interval?

1. 0.01

2. 0.005

3. 0.02

4. 0.001

The correct answer is: 0.005

In the context of statistical hypothesis testing and confidence intervals, the alpha error, often denoted as α, represents the probability of rejecting a true null hypothesis (Type I error). When working with a symmetric uniform distribution and a confidence interval of 0.99, this means that we are estimating that 99% of the data falls within this interval. Consequently, the remaining area outside the confidence interval represents the alpha error. Since a 0.99 confidence level implies that there is 1% of the data that falls outside the interval, this 1% is split between the two tails of the distribution. Therefore, you would allocate 0.5% (0.005) to the lower tail and 0.5% to the upper tail. This results in an alpha level of 0.005 for each tail. Thus, in the case of a symmetric uniform distribution, the correct measure of alpha error for a 0.99 confidence interval is 0.005. This reflects the reduced risk of making a Type I error at a high confidence level, establishing a clear understanding of how confidence intervals are formulated and the implications of alpha in hypothesis testing.