00:01
So in this question we're dealing with sampling techniques, right? so let's go over them quickly.
00:07
We have cluster sampling, where researchers divide a population into smaller groups in those clusters, and then they randomly choose some clusters, and this is usually used for larger populations.
00:17
Next, we have convenient sampling, which is a method of collecting samples by taking samples that are conveniently located around a location or an internet service.
00:25
Then we have stratified sampling, which is only take a stratified sample.
00:28
So researchers divide a population into subpopulations called strata, and this is based on specific shared characteristics, right? and at least one person from every strata is selected.
00:40
We also have systematic sampling.
00:41
Researchers select members of a population at a regular interval.
00:45
We also have simple random sampling, which is a type of probability sampling, in which the researcher randomly selects a subset of participants from a population.
00:53
Okay? so we're going to go through all of our scenarios where we're supposed to apply these sampling.
00:59
Methods.
01:00
Start with number one.
01:02
We are told that the researcher picks 20 different small groups.
01:05
A church group, a democrat club, a student club, etc.
01:08
Each of them contained 100 people.
01:11
And then the researcher makes sure everyone from each group answers the survey set, the question, right? so you can see that this is obviously going to be a straight disorder situation, right? because all these people have a shared characteristic and we're choosing at least one person from all of those groups gets to answer the question...