00:01
All right, so on this question, we are given a p value of 0 .01.
00:07
And we're doing kai squared.
00:09
It gives us a kai squared value of 13 .36.
00:13
So know that a kai squared curve is going to be skewed to the right in some way, maybe strongly skewed, maybe a little bit more symmetric.
00:21
And we have gotten a 13 .36 on our kai squared, and our p value is always going to shade to the right, and that area under the curve is 0 .01.
00:31
And we're looking at an association between income and education levels.
00:45
We're looking, is there an association? so our null hypothesis, it would be that income and education are not associated.
00:56
I think we probably know that's really not going to be true.
00:59
And then our alternate is that they are associated.
01:07
So basically what we're doing when we calculate a p value is we are assuming the null.
01:12
Is true.
01:13
It's almost like a proof by counter example, except for it's not really a proof.
01:16
You're just looking for evidence.
01:17
But you're looking for evidence by assuming that you have no evidence and seeing where your sample falls out...