00:01
Hello, welcome to the video, and today we're going to be talking about hypothesis tests, and specifically how to know when our evidence does or does not sufficiently support our claim.
00:11
So in this problem, it's worded really strangely.
00:14
It's written like a shakespeare script, but basically we have hamlet, who's trying to figure out how many of his classmates believe in ghosts.
00:26
So it is proposed that the proportion of the students who believe in ghosts is at least 75%, so we can translate this into a null hypothesis here by saying that x, which is just what we're going to call the proportion of students who believe in ghosts, is greater than or equal to, which is the same thing as at least 0 .75, the proposed proportion here.
00:55
And it is suspected that this number is not accurate, that it is too high.
01:00
So we can create an alternative hypothesis from that by saying that x is instead less than the proposed value of 0 .75.
01:10
So if we look at this, if we imagine this visually, we have a distribution over here with a peak value at the proposed x value of 0 .75.
01:20
And it is being claimed that the true value of x is either at 0 .75 or it could be somewhere over here, but we hope to find evidence during our hypothesis test that shows the true value.
01:38
It might actually be somewhere over here, and this would show that 0 .75 might not be the best representation of what x truly equals.
01:49
So we're going to be testing these hypotheses at a 5 % confidence level here.
01:57
And we, so in the problem, they take a sample to find a proportion...