00:01
All right, so for this problem, we'll first basically go through a little bit of a flow chart for figuring out what kind of test we want to use.
00:07
So we'll note that we are testing for means, or specifically testing for differences or for mean difference, for difference in means.
00:22
So that's our starting point.
00:26
This will then branch based on a first decision.
00:34
And that is, are the population standard deviations known? or unknown.
00:45
So we'll just say sigma 1, sigma 2 known, or question mark.
00:51
If sigma 1 and sigma 2 are known, then we would go into one of the varieties of z -test.
00:56
But in this specific example, we are told that the population variances, oh, actually we're referring to variances here, but in this case, we know that we know that we do not know the population variances, so we'll be going down the unknown branch.
01:13
When we go down the unknown branch, we go down the unknown branch, that means that we know that we'll be doing one of the kinds of t -test.
01:20
Then, from the fact that we'll be doing a t -test, we'll have to ask, are the samples independent or dependent? in other words, independent or paired...