00:01
So, first, we have our null hypothesis, which is that the theta equals 25, and then we have our alternative, which is that theta is less than 25.
00:18
The random samples from a normal distribution with a mean of theta and a variance of 16.
00:24
So xi is n of theta comma 16.
00:28
And the likelihood ratio test statistic, which is this delta of x, is pi of n to the i equals 1, f0 of xi, over pi of n to the i equals 1, f1 of xi, where f0 of xi and f1 of xi are the probability density functions.
01:02
For a normal distribution, we have the pdf, which is f of x given u comma standard deviation squared is 1 over root of 2 pi standard deviation squared times e to the negative x minus u squared over 2 standard deviation squared.
01:37
So when the pdf, or f0 of xi is the pdf when theta equals 25 and f1 of xi is the pdf when theta is less than 25.
01:48
So let's solve.
01:50
So the neyman -pearson -lima, so just the null hypothesis, is now characterized by, call this delta of x less than k...