Rather, it is a measure of the amount of scatter about the line. We will talk about this a lot more in the second class. This one gave many people trouble. Most people understand alpha, or probability level, quite well. It is also known as Type 1 error, or the likelihood that you have rejected a true null hypothesis.
Power is the probability of rejecting a false null.
This is known as Type 2 error. Precise calculation of power uses sample size and variability. Power is equal to 1-beta, and it can be increased by increasing the sample size or decreasing the variance. See Power, above. As to whether it's good or not, I can only give you the proverbial it depends .