Curious about the techniques researchers use to gather data effectively? You’ve come to the right place.
Sampling methods play a crucial role in the research process. Sampling lets you draw accurate conclusions about a larger population based on a smaller set of data.
In this article, we’ll explore the types of sampling methods commonly used in research, each with its own unique strengths and applications. Ready to enhance your research skills? Let’s dive in!
What is sampling?
Suppose you want to study a community of 10,000 people. Collecting data from all those thousands of people isn’t feasible, but taking a smaller group of 50-100 people is! These 50-100 people are your sample, and they represent the entire population.
Sampling is the process of selecting a smaller group of subjects to study. It’s a fundamental technique used in research, but because there are many ways to select a group, there are different sampling methods. The method used can differ based on the nature of the study.
Population vs. sample
What’s the difference between a population and a sample in research?
Population is the larger entity under study that you want to draw conclusions about. The sample is the smaller subset of people you’ve selected to represent the population in your study.
In the above example, the 10,000 community members comprise the population, and the 50-100 people selected for the study are the sample.
How do I collect data from sample?
Once you’ve successfully selected your sample, the next stage is data collection. Data collection can involve surveys, interviews, experiments, and more. It can be an intimidating step, but with the help of the right tools, it’s a breeze.
One of the best ways to collect data is with surveys, and no platform is better for online surveys than Google Forms. It’s free to use and very intuitive, meaning anyone who wants to conduct research can use it. You can easily make your own Google Form to suit your data collection needs.
Even better, you can use Google Workspace add-ons to make Google Forms even better. Use Form Publisher to automatically create response summaries and store them in the appropriate folders. Use Advanced Summary to extract better data from your forms through the use of filters and more in-depth charts.
What are the types of sampling?
Sampling methods can be broadly classified into probability and non-probability sampling. Let’s learn about each.
Also known as random sampling, probability sampling is a method of selecting a sample from a population where each member has a known and equal chance of being chosen.
It's like a fair lottery, ensuring that everyone in the group has an opportunity to be selected for the research, improving the accuracy of the results. It can be further split into four types.
Simple random sampling
Simple random sampling is a way of picking a sample from a group where members are randomly chosen. It's like drawing names from a hat. This is very easy to pull off, and it’s great for research that values the random aspect of the sample.
This is a method of selecting a sample from a larger group by choosing every “nth” member. For example, if you want a sample of 10 from 100 people, you might pick every 10th person. It's like creating a pattern to ensure a representative sample without it being completely random.
In this sampling method, a large group is divided into smaller, more manageable subgroups based on specific characteristics, like age or gender. Then, a sample is randomly taken from each subgroup to ensure a diverse representation of the entire population in the research.
Cluster sampling is a method where the large group is divided into clusters or smaller groups. Then, rather than picking from each cluster, as in stratified sampling, a few whole clusters are randomly chosen, and all members within those clusters are included in the sample.
In this sampling method, each member of the population doesn’t have an equal chance of being selected. Researchers use their judgment to handpick participants. There are chances of bias in this type of sampling method. It can be further classified into four types.
In this method, researchers select a sample based on easy accessibility or convenience, and readily available participants are preferred. For example, individuals are chosen based on proximity and internet access when surveying people. It's quick and straightforward but may not represent the entire population accurately.
Purposive sampling is when a sample is selected with a specific purpose or criteria. Researchers intentionally handpick participants that match particular characteristics relevant to the study.
This method of sampling ensures they provide valuable insights about a specific group. It's useful for targeted research but may limit generalizability to the entire population.
Snowball sampling allows participants to refer others to join the research, creating a chain-like effect. It starts with a small group of initial participants who recruit others with similar traits or experiences.
This approach is ideal for studying hard-to-reach or hidden populations, like rare medical conditions or marginalized communities.
Quota sampling is a method where researchers divide the population into subgroups based on specific characteristics. They then set a quota for each subgroup and collect data until it is met.
It's like ensuring a proportional representation of different groups to simplify the sampling process without random selection.
Research better with Google Forms using Advanced Summary
Now you know all about the different types of sampling methods in research and the tools that can make your research easier. No matter what sampling methods you employ, Google Forms and Advanced Summary can help you make it better. Google Forms is the best and most intuitive online form creation platform for your data collection needs, and Advanced Summary can supercharge your data analysis process. Try it out today!