Final answer:
An alpha level is the probability of a Type I error in hypothesis testing.
Step-by-step explanation:
An alpha level is not the same thing as dividing a probability by two. It is the probability of a Type I error, which is the probability of rejecting the null hypothesis when the null hypothesis is true. It is denoted by the Greek letter α.
For example, a common alpha level used in hypothesis testing is 0.05, which means that there is a 5% chance of making a Type I error. If the calculated p-value is less than 0.05, we reject the null hypothesis.