Final answer:
An example of the level of significance is a threshold of 5% (0.05) for rejecting or accepting the null hypothesis in statistical testing, which defines the probability of making a Type I error.
Step-by-step explanation:
An example of the level of significance is when a statistician prescribes a threshold, such as 5% (0.05), for accepting or rejecting the null hypothesis in a statistical test. This threshold represents the probability of committing a Type I error, which is rejecting a true null hypothesis. When the level of significance is set to 0.05, if the p-value obtained from the statistical test is less than 0.05, the null hypothesis is rejected, and it is concluded that the results are statistically significant.
For instance, consider a study comparing male and female college students' living arrangements, using a level of significance of 0.05. If the p-value from this test is lower than 0.05, we would conclude that there is a significant difference in living arrangements based on gender. It's essential to choose an appropriate level of significance before beginning the study to avoid bias in the results.