00:01
We have been given a confidence interval 41 .9, 43 .8.
00:08
So how can we interpret this? so this is a confidence interval for the population mean, okay? so i'm going to start by explaining how we get these.
00:22
There's some mean mu that we want to know, but it's not reasonable to ask everybody in the country how many hours they work.
00:30
So we take a sample and we find the sample data, and we get x bar, the sample mean.
00:36
But the probability of x bar being exactly the same as mu is infinitesimally small.
00:42
So we need to have an idea of how close the sample mean will be to the population mean.
00:49
So what we do is we make a sampling distribution.
00:53
So this is approximately normal, since the sample size is over 30.
00:58
And what we do is we make an interval inside this distribution containing 95 % of the area of this curve.
01:08
So this curve is representing the probability of getting different sample means if the population mean is mu.
01:15
So now 95 % of the time the sample mean will fall inside this interval.
01:21
So if you put x bar, 95 % of the time it will be in the interval, 5 % of the time it'll be in one of these tables.
01:29
Let's say hypothetically it falls here.
01:32
Now we take this interval, keep it the same length, but we just shift it to center on x bar like so.
01:42
And of course mu is in the interval, x bar isn't far enough away to be outside the original interval.
01:48
So if we shift it, mu is in the confidence interval.
01:52
And that's going to be true 95 % of the time...