1137 LearnersLast updated on June 18th, 2025
Methods of Sampling
The various sampling methods we use to collect data for different types of samples in statistical analysis are known as sampling methods. We use different methods to select an accurate sample from the population for analysis. In this topic, we will discuss the sampling method, its types, applications, and differences.
What is Sampling?
Sampling is the technique used in statistical analysis to pick out the number of observations from a larger population. It helps the researcher to use a small group of people from a larger population, if the sample is not precise, then it can result in inaccurate results. It is used in the fields of statistics, psychology research, sales, and the financial industry.
To get a conclusion about populations from sample research, researchers use sampling. Sampling is required to select a sample from a large population, as the size of a sample is small, it is more practical than analysis of the entire population.
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What are the types of sampling
Now, let’s learn about the types of sampling that can be classified into probability sampling and non-probability sampling. We will now learn what probability sampling and non-probability sampling are and their types.
| Probability sampling | Non-probability sampling |
| Simple Random Sampling | Convenience Sampling |
| Cluster Sampling | Judgmental or Purposive Sampling |
| Systematic Sampling | Snowball Sampling |
| Stratified Random Sampling | Quota Sampling |
Probability Sampling
Here, the samples are randomly selected from the data set. Each entity of such a population has an equal chance of being selected to be part of the sample. The types of probability sampling are:
- Simple Random Sampling
- Cluster Sampling
- Systematic Sampling
- Stratified Random Sampling
Simple Random Sampling
When the members of the population have an equal chance of being selected, it is known as simple random sampling. It is purely based on chance. It is the most direct method of probability sampling.
Systematic Sampling
In this type of sampling, the population is given a number, and the first individual is selected randomly, and the other is selected from the fixed intervals.
Stratified Random Sampling
Here, the population is divided into subgroups based on traits such as age, gender, category, and so on. And from each group, we select samples.
Cluster Sampling
In this type of sampling, the population is divided into subgroups, which are known as clusters. The sample is selected from each cluster or group, not from the population.
Non - Probability Sampling
In this method, the samples are selected based on certain criteria; it is a non-random sampling technique. The types:
- Convenience Sampling
- Quota Sampling
- Judgment Sampling
- Snowball sampling
Convenience Sampling
In this method, the data collection is dependent on their ease of access. Here, the sampling is used when initial data needs to be collected inexpensively.
Quota Sampling
In this sampling method, the data is collected based on the predetermined characteristics of the population. In quota sampling, the sample cannot be the best representation of the characteristics of the population.
Judgment Sampling
Here, the sample is selected based on the judgment of the experts. The experts choose who to ask to participate. It is also known as selective sampling.
Snowball sampling
Here, a few people are asked to nominate more people known to them, so the sample size increases. And it rotates like a snowball.
What are the steps for Sampling
Now let’s learn the step-by-step process of sampling.
Step 1: Identify and define the target population
In this step, the researcher will identify and define the target population.
Step 2: Selection of sample frame
In this step, the researcher will do the sampling frame, that is, they will create a list of people or items of the population from which the sample is taken.
Step 3: Selecting the sample method
Here, based on the type of population, the researcher will decide on the sampling method such as probability sampling or non-probability sampling, and so on.
Step 4: Choosing the sample size
We decide the sample size based on the population, that is, the sample size should be able to make inferences about the population.
Step 5: Collecting the data
After all these processes we will have a perfect sample for the research, that is now we are left with only collecting data.
Difference between population vs. sample
Do you know what is the difference between population and sample? If not let’s learn it together, here are the differences between population and sample
| Population | Sample |
| Population is the group about which the conclusion is drawn | The sample is a specific group from the population that we use for data collection |
| It is about every unit of the group | It is only about the small units of the population |
| Use to understand a group of people | It is a sample of the survey |
What are the Advantages and Disadvantages of Data Sampling Methods
Now let’s learn about the advantages and disadvantages of data sampling methods
| Sampling Method | Advantages | Disadvantages |
| Random Sampling |
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| Stratified Sampling |
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| Cluster Sampling |
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Real-world applications of Sampling
In various fields we use sampling to collect information from an entire population. Let’s discuss a few real-world applications.
- In marketing we use sampling to conduct research on market trends, customer preferences, purchase behavior and so on.
- Researchers use sampling techniques to study about the nature and pollution level
- In factories random sampling methods are used to inspect the small batch of products to identify the defect products.
- To improve the curriculum and teaching methods, student feedback surveys are used.
Common Mistakes and How to Avoid Them in Sampling
While collecting data students tend to make some mistakes, most mistakes occur while sampling. Now let’s learn a few mistakes and ways to avoid them in sampling.
Mistake 1
Using a small sample size
If a small sample size is used it can lead to wrong conclusions and unreliable results. So it is important to calculate the required sample size for a better understanding of the sample.
Mistake 2
Using the wrong method of sampling
For each research question and the type of population, there are different types of sampling methods. Sometimes students use inappropriate methods of sampling. So students should understand the type of research question and the type of population before choosing the sample method.
Mistake 3
Using an old sampling frame
Using an old sampling frame will not reflect the current population, which can lead to coverage errors. So it is significant to regularly update the sampling frame for getting the latest information.
Mistake 4
Errors while data entry
Errors in data entry while collecting information can lead to error in conclusion. So it is essential to recheck the data entry and do the quality control audits on the data.
Mistake 5
Surveying only easily accessible subjects
When doing surveys that relies on easily accessible subjects can lead to biased results. So it is essential to select the right population and sampling method.
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Solved Examples of Sampling
Problem 1
A school wants to survey student satisfaction. There are 1,000 students, but the school selects 100 students randomly. What type of sampling is used?
The sampling method used is simple random sampling
Explanation
Here, each of the students has an equal chance of being selected from the population. The students are selected randomly, so it is a simple random sampling.
Problem 2
A company has 500 employees divided into five departments. The management selects 20 employees from each department for feedback. What sampling method is this?
The sampling method used is stratified sampling
Explanation
The employees are first divided into subgroups, and then a fixed number of employees are chosen from each subgroup. Moreover, each department has an equal number of employees, so it is a stratified sampling
Problem 3
A supermarket wants to analyze customer feedback. They decide to survey every 10th customer who enters the store. What sampling technique is used?
The sampling method used is systematic sampling
Explanation
The customers are selected using a fixed interval, so it is systematic sampling as it has a structured approach to selection.
Problem 4
A company posts an online survey on social media and collects responses from volunteers. What sampling technique is being used?
The sampling method used is voluntary response sampling
Explanation
Here are the individuals who voluntarily decide to participate. So, it is a voluntary response sampling.
Problem 5
A government agency wants to study farming practices across different villages. They randomly select 10 villages and survey all farmers in those villages. What sampling method is used?
The sampling method used is cluster sampling
Explanation
Villages are considered clusters. The government agency randomly selects a set of clusters and surveys every farmer within those selected clusters, so it is a cluster sampling
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FAQs on Sampling
1.What is sampling in research?
2.What are the main types of sampling?
3.What are the common probability sampling methods?
4.What are the common non-probability sampling methods?
5.What is non-probability sampling?
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Jaipreet Kour Wazir
About the Author
Jaipreet Kour Wazir is a data wizard with over 5 years of expertise in simplifying complex data concepts. From crunching numbers to crafting insightful visualizations, she turns raw data into compelling stories. Her journey from analytics to education ref
Fun Fact
: She compares datasets to puzzle games—the more you play with them, the clearer the picture becomes!
