The researcher has determined the project has an alpha level of 0.05. This indicates all values outside ____ will be rejected.

When a researcher sets an alpha level of 0.05, they are defining a threshold for significance in hypothesis testing. This level indicates that there is a 5% probability of rejecting the null hypothesis when it is, in fact, true, which is commonly referred to as a Type I error.

In a typical statistical test, the alpha level delineates the critical region where the null hypothesis will be rejected. Specifically, an alpha of 0.05 means that any test statistic that falls into the most extreme 5% of the distribution will lead to the rejection of the null hypothesis. In terms of confidence intervals, an alpha of 0.05 corresponds to a 95% confidence level, signifying that if the null hypothesis is true, there is a 95% chance that the observed data would fall within this region.

Therefore, the correct articulation of this concept is that all values outside the 95% confidence interval will be rejected, aligning with the definition of the alpha level. This coupling of alpha with confidence levels is fundamental in interpreting the results of hypothesis testing effectively.