00:01
So this is a question effectively about the central limit there, and we just need to know what the central limit theorem says.
00:06
And this is one of the most powerful results in statistics that you just have to memorize.
00:09
The central limit says, one, if you have a sample size of greater than 30, or if x is equal, is normally distributed, that is the underlying population is normally distributed, then the sample mean is distributed normally and inherits the underlying population mean and has a standard error proportional to the noise in the underlying population over the square root of n, right? where this square root event says, when you have a sample, you have more statistical power, so the noise of your estimate is decreasing.
00:39
So we're given three pieces of information here, right? no outliers.
00:46
This is irrelevant.
00:48
The clt doesn't say anything about outliers, right? there's nothing here about this inference procedure only works if there are no outliers or anything like that.
01:01
There's absolutely nothing here.
01:04
Two, n is equal to 250...
