00:01
When we talk about critical and non -critical regions, we're referring to the areas under the bell curve that we would either reject or fail to reject the null hypothesis whenever our test statistic lies in that region.
00:16
So, for example, we would have a bell curve that looks something like this when we talk about our population.
00:23
Then we would go out and we would conduct a survey and get a sample to get a mean from that population.
00:31
Population.
00:33
So let's say our sample mean is somewhere out here, then most likely that would be far enough away from our mean that we would reject the null hypothesis.
00:46
So it's all going to depend on what level of significance we choose.
00:51
If we choose 90%, then the cutoff point will probably be something closer to here.
00:59
Whereas if we did a 99%, percent it'll be probably out more like here.
01:08
However, a lot of times we will do a 95 % with a two -tailed test and it'll be 1 .96.
01:19
That's probably the most common cutoff point is 1 .96, which should be around here.
01:26
And so in that case, anything that is in this shaded region would be the reason, would be the region where we would reject the null hypothesis...