00:01
Okay, so the whole idea of a p -value, right, is you have your null hypothesis and you have a distribution under your null hypothesis.
00:08
And you have some value, some alpha, right, that you set usually 0 .05.
00:15
And you say that if you have a p -value less than that alpha, then you reject, right? so say that this is the p -value here.
00:25
Okay.
00:25
If that is less than 0 .05 than you reject.
00:31
Okay, so the larger your z, right, or the farther away from the null hypothesis your z is, the more likely you are to reject.
00:44
Okay, so in 31, if the absolute value, if the of the calculated z value is less than the critical value, so that would be like if it's over here, you would fail to reject.
00:56
Okay, you would fail to reject the null.
01:00
You never, ever, ever accept the null.
01:02
You just fail to reject it.
01:06
In the p -value approach, if the calculated z value is 2 .27 for a two -tailed test.
01:11
So a two -tailed test looks like this that i wrote, except for you have p -values on both sides.
01:17
So you have to look up the area for z equals 2 .27.
01:26
Okay? and so when i look up the value for z equals 2 .27 i get 0 .016, so you have to multiply that by 2...