In population and sample,

there are certain important statistical measures which you have to remember.

First, when you’re looking at the population,

the first element of the population is the population mean.

What is the population mean?

Population mean is the measure of central tendency in the population.

The second important thing for a population is the population variant or,

for that matter, population standard deviation.

This is the measure of variation in the population or

between the units of the population.

When we look at a sample instead of a population,

we have to also consider a few statistical measures which are important to consider.

First of all, is a sample mean.

What is a sample mean?

Sample mean is noting but

an estimate of the population mean, which you do using your sample elements.

The second important thing is your sample variance or for

that matter sample standard deviation.

Sample standard deviation is the estimate of the population variance or

the population standard deviation as the case may be.

Now once you look at the sample mean and the sample standard deviation,

you have to also consider what are the variation in the sample mean?

So variation in the sample mean is basically captured through

standard error of the sample mean.

Finally, when you're drawing a sample, you have to look at the confidence interval

of the sample mean, this determines the reliability aspect of the sample.

So basically,

if you have a unreliable sample, your confidence interval will be larger,

whereas if you have a reliable sample, your confidence interval will be narrower.

Now, we start looking at, the different sampling plans,

which researchers use when drawing a sample.

The first type of sampling plan is called probability samples.

Here, under probability samples, each unit, which you select from

your population in the sample, has a known probability of being included.

This, an example of probability sample, is a simple random sample.

In this kind of sampling procedure your sampling error,

remember we discussed about how calculate the variation, this sampling error can

actually be inferred in terms of a mathematical quantity.

The second is you usually definitely need a sampling frame

while drawing a probability sample.

However, because this method is more formal, it requires more funds.

So it's usually more expensive than the other type of sampling procedure,

which is called non-probability samples.

Now, under non-probability samples,

the probability of units being included in the sample is not known.

What is an example?

Think about you being stopped in a mall for a survey.

A mall intercept is example of a non-probability sample

because you are just picked randomly

from a population of people who are walking around in the mall.

In this case, under non-probability sample,

the sampling error cannot be inferred because, in most cases,

a sampling frame is not used under non-probability sample.

Of course, this kind of sampling is done in a rather ad hoc manner.

For that reason, often it's much less expensive than any other

sampling procedure, especially compared to probability sample.

We are going to talk about different probability sampling procedures

in the next video, so looking forward to talking to you then.

Thank you.

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