00:01
All right.
00:01
So we're looking for the critical value for a right -tailed t -test.
00:06
So a lot of things we need to know in order to do the t -test.
00:11
The first thing we need to know is our degrees of freedom, which is always going to be n -1.
00:16
And that tells us which t -distribution we're going to use.
00:22
So the t -distribution is symmetric, not the same as the z distribution we would use, like for a normal curve.
00:30
But as the degrees of freedom, which is the sample size, goes up, it becomes more and more like the z curve or the standard normal distribution.
00:47
So we do have an approximately normal.
00:50
We can still use sort of distribution kind of like that, but we are needing, it's a little bit different because it's going to be with a smaller sample size.
00:59
It's going to be the spread is going to be a little bit wider than the z curve that we're used to but to get the so if we have a right -tailed test all right let's say we're using an alpha of 0 .05 that's the most common that means that our rejection region is going to happen 5 % of the time and our um the non -rejection region the fail -to -reject region is going to be 95 % of our curve we know that those add up to one because of our, because that's a density curve, any density curve adds up to 100%.
01:38
So if the alpha is 0 .05, the area to the left of that is 0 .95.
01:43
So let's say, with an example, let's say that we had a sample size of 35.
01:51
Okay, that means that our degrees of freedom is going to be 34.
01:55
And the best way of doing this is to use a graphing calculator.
01:59
And we're going to do inverse t.
02:02
All right, so i'm going to go to my graphing calculator and do inverse t...