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Hey guys, in this video, we are going to talk about the difference between sample and population.
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And then we're also going to touch a little bit on different sampling methods.
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Okay, so the first thing we need to see, and i have this little visual for y 'all, the population is everything, and the sample is made up of that population.
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So here we have an example.
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A polling organization contacts 2 ,141 male university graduates who have a white -collar job and asks whether or not they had received a raise at work during the past four months.
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Now we have a lot of extra information that we don't need.
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However, here we have the population.
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It's going to be instead of the 211 male university graduates who have a white -collar job, it's going to be all of those male university graduates with a white -collar job.
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And the sample is just the 2141 that they talked to.
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Next, we have a quality control manager randomly select 70 bottles of cousins.
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That were filled on july 17 to access the calibration of the filling machine.
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All right.
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Our population, it's going to be not those 70 bottles, it's going to be all of the bottles of ketchup that were filled on july 17.
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Not all of the bottles that were filled total just on july 17.
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All right, and that sample is going to be those 70 bottles on july 17th.
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The last example we have for this is the current population and report.
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Report from the psa.
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All right.
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It's based on a survey of 50 ,000 households in the philippines.
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Okay, our population is going to be every household in the philippines.
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And the sample is just those 50 ,000 that they surveyed.
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All right, so i hope that clears things up for people.
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Next, we're going to talk about the different types of sampling.
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Okay, we have stratified, we have cluster, we have systematic, and we have simple random sampling.
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There are so.
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Certainly more types of sampling, but these are the four that we're going to talk about for right now.
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So let's first talk about stratified sampling.
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All right.
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So in stratified sampling, you split your population up into different strata, and that's going to be right.
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That's going to be shown with these three circles here.
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And then what happens is you're going to take a couple from each of these strata to form your sample.
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And you're going to do that by simple random sampling, which we'll talk about later.
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So we're going to do an srs to get the sample here.
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Okay? in clustered sampling, we're doing a similar thing.
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We're going to divide our population up into these clusters.
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All right.
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But instead of taking a simple random sample of each cluster, we're going to randomly select one whole cluster to be our sample.
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All right...