Final answer:
The level of significance (alpha) is the threshold used to determine the statistical significance of an observed effect in hypothesis testing, representing the risk of a Type I error, where a true null hypothesis is incorrectly rejected.
Step-by-step explanation:
The level of significance (alpha) in analytical studies where groups are compared and differences are assessed, is a threshold for deciding whether an observed effect is statistically significant. This alpha level represents the probability of committing a Type I error, which occurs when the null hypothesis is incorrectly rejected.
A commonly used level of significance is 5%, but in some studies, researchers might use a more stringent level such as 1%. For example, using a significance level of 1 percent, if we were to examine the mean grades among sororities and find the p-value to be higher than 0.01, we would not reject the null hypothesis, indicating there is not enough evidence to conclude a significant difference in mean grades.