Welcome back. With today's technology,

discovering the ideal sample size is easy.

But you need to apply these calculations to include

specifics of the population you want to include,

like their geography, habits and other demographics.

So after this lesson,

you will be able to determine the appropriate sample size for your survey,

so you have the best chance of finding significant results.

Let's get started.

When we talk about determining

the appropriate sample size and quantitative market research,

we mean getting to a particular group of people within

a population who meet our criteria for inclusion.

It is a set of participants selected from the population which

is less in number or size but adequately

represents the population from which it is drawn so that

the true inferences about the population can be made from the results obtained.

This set of individuals is known as the sample.

Again, population is defined as the complete set of people, for example, Indians.

Target population is a subset of individuals with

specific clinical and demographic characteristics

with whom you want to study your intervention.

For instance, males between age 45 and 60 with blood pressure between 140.

And a sample is a further subset of

the target population which we would like to include in the study.

Thus, a sample is a portion or piece or segment that is representative of the whole.

The criteria for the sample is that, one,

every individual in the chosen population should

have an equal chance to be included in the sample,

two, the choice of one participant should not affect the chance of another selection.

Hence, we try to select the sample randomly.

Thus, it's important to know that random sampling does not describe the sample

or its size as much as it describes how the sample is chosen.

In order to calculate the optimum number of participants required to

be able to arrive at ethically and scientifically valid results,

the principles and methods used to calculate the sample size

depends on the acceptance of the level of significance,

the power of the study,

the expected effect size,

the underlying event rate in the population,

and the standard deviation of the population.

In actuality, there is no standard sample size.

The sample size you need is entirely dependent on the nature of your research questions.

What are you hoping to achieve with

your study and the resources that are available to you?

Determining sample size is very important

because samples that are too large may waste time,

resources, and money, while samples that are too small may lead to inaccurate results.

In many cases, we can easily determine the minimum sample size needed

to estimate a process parameter such as population mean.

If you took course one in this specialization,

you may recall that Jim Fong discussed finding the appropriate sample size.

Since some of the learners are starting with this course, let me refresh.

You need to know the criteria you're applying to determine sample size.

In quantitative research, you want it to be scientifically viable to industry standards,

that would be to aim for error margin of plus or minus 5% at 96% level of confidence.

So, if your client specifies that they want 1,000 responses total,

the norm from response rates for online surveys is 85%.

So, if 85% of 1,180 equals 1,003 responses,

you should plan on emailing at least that

many people to get what your client hoped to have.

Everyone is familiar with the p-value.

This is the level of significance and prior to starting a study,

we set an acceptable value for this p. When we say, for example,

we will accept a p of 0.05 as significant,

we mean that we are ready to accept that the probability that the result is

observed due to chance and not due to our intervention is 5%.

These are important aspects to consider when choosing a sample size.

There are many good sample size calculators available for free online.

A couple that are brought up when you type in sample size calculators into Google,

are ones offered by the National Statistical Service and one Survey Monkey.

For both, you just plug in your relevant numbers.

You can use the tool of your choice or better yet,

try using several to see if you have a preference.

They all do pretty much the same thing.

You enter the confidence level you want,

the population size, the proportion of relevance standard error.

You must fill in one of the confidence intervals; Standard Error,

Relative Standard Error or Sample Size,

and then press Calculate.

The result will be the ideal number you need to meet all the criteria you entered.

Now that you've completed this lesson,

you should be able to determine the appropriate sample size

for any project where you are creating a quantitative survey.