00:01
Type 1 and type 2 errors refer to when we incorrectly state the results of a hypothesis test.
00:08
A type 1 error is a false positive, or in other words, when we incorrectly reject the null hypothesis.
00:18
A type 2 error is a false negative, or when we incorrectly fail to reject the null hypothesis.
00:30
So this would be the type 2 error's definition.
00:35
Now, when we do a hypothesis test, we'll say something along the lines of we are 95 % confident in the results, and that would be our alpha level.
00:52
This means that if we get a p value of, for example, 3%, or 0 .03, then in this case we would want to reject the null hypothesis, because our p value, tells us the probability that our null hypothesis was correct.
01:12
Since it's a very low chance of having a correct null hypothesis, we would reject it in this situation...