00:01
The first question here asks whether the p -value of a hypothesis test gives the probability that the null hypothesis is true.
00:11
And this is false.
00:14
When we do a hypothesis test, we initially assume that the null hypothesis is true.
00:20
And if the null hypothesis is true, our test statistic would follow some distribution under this assumption.
00:27
It could be a kai square distribution or a normal distribution, or a t distribution depending on what we are testing for and what information we have.
00:37
Let's say our test statistic follows a t distribution.
00:41
This is how this distribution would look under the null hypothesis.
00:48
And let's say our test statistic comes out to this value.
00:54
It's called that t sub test.
00:57
The p value is the probability of getting a test statistic at least this extreme under the assumption of the null hypothesis.
01:05
So this is the p value.
01:09
So the p value just gives you an idea of how imprompt probable our test statistic is under the null assumption.
01:18
The smaller the p -value, the less probable our test statistic is, which makes us more inclined to reject the null hypothesis...