Types of Sampling Methods in Statistics

As you saw in the last section, it is important to understand the process of sample data collection. For this, you will need to explore the various sampling methods.

Generally, these sampling methods are categorised into four types. Let’s listen to Ujjyaini as she explains what these four types are and how and when they are used.

As you just learnt, there are four types of sampling methods/techniques, as depicted by the following image.

These four types of sampling methods are:

1. Random Sampling: In this method, people in the sample are selected randomly. This is similar to randomly pulling names out of a hat.

Example: Suppose you want to find out the average internet usage per person in India. You just put the names of all the Indians in a hat and pull out 100 names at random, and then calculate the average internet usage of these 100 Indians.

2. Stratified Sampling: Here, people are divided into subgroups and then selected randomly from those subgroups. But this is done in such a way that the final sample has the same proportions of these subgroups as the population.

Example: Again, suppose you want to find out the average internet usage per person in India. Note that 70% of Indians live in rural areas, and 30% live in urban areas. So, you would put the names of all the rural Indians in hat A and the names of all the urban Indians in hat B. Then, you’d pull 70 names out of hat A and 30 names out of hat B. Now, again, you’d have a sample of 100 Indians, but this time, your sample would be more representative of the population as its rural and urban proportions would be the same as that of the population.

3. Volunteer Sampling: Here, your sample is composed of people who want to volunteer for the survey.

Example: Suppose that once more, you want to find out the average internet usage per person in India. You could ask people to take an online survey, which asks them how often/much they use the internet. You could ask the same question through a telephonic survey.

The good thing about this type of sampling is that it looks unbiased and random because the survey participants are selected at random through the medium (internet, telephone) itself. There is no human interference. However, the medium will also bring in some bias. For example, an internet survey is more likely to include people who have high internet usage, whereas a telephone survey is a little more likely to have a balanced representation of heavy internet users and people who use the internet infrequently.

4. Opportunity Sampling: In this method, the people around and close to the surveyor form their sample space.

Example: This time, when you want to find out the average internet usage per person in India, you just ask 100 people around you about their internet usage.

Clearly, this sampling method has the potential to become extremely biased. The only good thing here, probably, is that this is a relatively convenient sampling method.