## What Are Sampling Techniques?

Sampling techniques are effective sampling methods used by survey researchers to infer information or draw meaningful conclusions from a subset of the population without investigating every individual. These methods are fundamental in data science, data analysis, educational research, environmental monitoring, statistics, market research, product development, and survey research. Numerous researchers and analysts in various fields and industries use different types of sampling techniques to save time and money while gathering high-quality information for their quantitative research studies.

The sampling process requires using a small number of components or portions of the population to create conclusions. For instance, researchers generalize about a specific group of people or subjects based on a small sample of observations or a subset of a particular population. Additionally, this process allows researchers to estimate several unidentified characteristics or traits of a population of interest.

## Types of Probability Sampling Techniques

Probability sampling techniques are cost-effective, simple, straightforward, and non-technical sampling techniques that use randomization to ensure that every component of the population has an equal chance to include in the selected sample. Also known as random sampling or representative sampling techniques, these methods select elements or traits such as test items, objects, and participants from a population. Researchers use probability sampling to make sure that the sample is representative of the population and to estimate the uncertainty level in the results, and to generalize the findings to the population.

Cluster Sampling: This type of probability sampling technique involves dividing the population into clusters or small groups and then selecting some of the small groups. It can be done in two ways: single-stage cluster sampling or two-stage cluster sampling. Clustering sampling is beneficial when the population extends over a large geographical area. Use this method if you want to randomly select participants that are spread out geographically and analyze a specific population in which the sample contains more than a few aspects such as family, city, school, and many others. For example, randomly choose from borderlines of areas such as districts or cities. Simple Random Sampling: This sampling technique is used by researchers when they want to select a sample from the population without any bias. As the most direct form of probability sampling, assign numbers to the individuals or the sample and choose randomly from those numbers using an automated process. The chosen numbers are the individuals that are part of the sample. The lottery system and the number-generating software or random number table are the two methods used by researchers when choosing the samples through a simple random sampling technique. Stratified Sampling: Researchers use stratified random sampling technique when they divide a more large-scale population into smaller groups that typically don’t go beyond but portray the whole population. They arrange or classify the individuals by age, ethnicity, sex, and other similar characteristics. Then, they split subjects into mutually independent groups and select members from groups using simple random sampling. Systematic Sampling: Use systematic sampling if you prefer to select every “nth” individual to be included in the sample. This means you need to choose each group member at regular periods to create a sample. The advantage of this sampling technique is that every member of a population has an equal opportunity. For example, the sample selection process may select every seventh person in a list. So, the sample selection in this technique depends on the position of the individual in the list.

## Types of Non-Probability Sampling Techniques

Also referred to as non-random sampling, the non-probability sampling technique is a type of sampling method used by researchers and survey analysts when they select units from a population using a subjective method. However, there are some challenges when they use this sampling because it is difficult to estimate the probability of any one element taken in the sample. Still, researchers use non-probability sampling techniques due to the decline in response rates in probability surveys, the expensive cost of data collection, the need for access to real-time statistics, and the rise of non-probability data sources including social media and web surveys.

Convenience Sampling: Also referred to as haphazard sampling, convenience sampling is a type of non-probability sampling technique used by researchers to select units randomly without planning as they consider that the population units are all similar and any unit may be selected for the sample. They select easily accessible individuals or people who are willing to join in their survey research study. For example, the researcher uses a survey form to be completed by the people coming into the business firm or a survey questionnaire to ask employees or customers about the products and services of the company.Snowball Sampling: This non-probability sampling technique is known as networking sampling, Market researchers and survey researchers use snowball sampling when participants required for the survey research are difficult to find. It is a beneficial sampling method for rare or hard-to-reach populations such as homeless people, drug users, people with disabilities, or other individuals who may not belong to an organized group or those who are not recorded on a survey list frame. For example, a researcher wants to search for rare individuals in the population as he or she contacts them and asks them if they know anyone similar to them, and then they contact those people. It is important for researchers using this sampling technique to get in touch with the person who will put them in touch with other people they need for the survey research. Purposive Sampling: This non-probability sampling technique is also called judgment sampling. With the purposive sampling technique, researchers use their previous knowledge of population composition and behavior when they select the units to be added to the sample. There will be some experts who are in charge of choosing purposely what is considered to be a representative sample. That’s why this sampling method tends to be more biased as large biases can be made if there are inaccurate preconceptions. But this is a useful sampling method if you want to work on exploratory studies. For example, use purposive sampling when you select members for focus groups or in-depth interviews to examine particular components of a questionnaire. Quota Sampling: One of the most basic forms of non-probability sampling techniques is quota sampling. This sampling technique is conducted until a certain number of units or quotas for wide-ranging subpopulations have been chosen. Use this method if you want to fulfill sample size objectives for the subpopulations. Somewhat similar to stratified sampling as similar units are grouped, quota sampling differs in how the units are chosen as market researchers use this specifically for telephone surveys to survey individuals with specific socio-economic profiles. Volunteer Sampling: It is also called self-selection sampling where the respondents are volunteers in the study. They are screened based on the characteristics suitable for the goals and objectives of the survey. A voluntary response sample is used in medical settings where individuals with specific medical conditions volunteer for some medical experiments. Crowdsourcing: Researchers use this non-probability sampling technique to allow the public who wants to contribute to solving a particular concern or issue. This method is used to solve a problem by freely sharing the answer with everyone. It is an innovative method to gather essential information for statistical purposes. In this way, surveys are accomplished quickly with less cost and response burden.

## How to Conduct a Basic Sampling Technique

There are many ways to carry out probability and non-probability sampling techniques. If you want to conduct the basic sampling technique, follow the step-by-step procedure in this section.

### Step 1: Specify the Population

Define the population with which you want to generalize your results for your survey research. Each study that you undertake has a different population of interest. Be clear and straightforward as the sample must be drawn from the population you want to generalize or the population you want to focus on.

### Step 2: Create a List

Prepare a comprehensive list of the population from which to choose your sample. Be careful when compiling a list or using one that is already made. The list should be recent and exhaustive which means all the members must appear on the list. Having a ready-made list is better quality and cost-efficient than a newly made list.

### Step 3: Draw the Sample

When you are done with the list of population members, use some rand sampling techniques such as using a table of random numbers and using computer programs. Don’t violate the random selection procedure and follow how to carry it out. Use the special functions of computer software like Excel to import the population lists into the database. Most database programs can generate a series of random numbers and a function for choosing a random sample from a range of entries found in the database.

### Step 4: Contact Members of a Sample

Contact each of those chosen for the sample and collect the necessary information. However, if you are encountering challenges in your survey, use other sampling methods or research tools to reach them.

## What are the different types of sampling techniques?

The different types of sampling techniques are cluster sampling, simple random sampling, stratified sampling, and systematic sampling.

## How to choose a sampling technique for research?

Choose a sampling technique for your research study or experiment based on the major goals and objectives of your work. For example, if you prefer to investigate for sampling bias, use a random sampling technique. Some examples of random sampling techniques are cluster, stratified, and systematic sampling.

## How many major sampling techniques are there in research?

There are two major sampling techniques used by researchers and analysts. These are probability sampling and non-probability sampling techniques.

## How to reduce the sampling error?

Use the sample error formula. Increase the sample size to yield a more accurate result and split the population into smaller groups. Apply random sampling and observe your target market for your survey campaigns.

It is integral to have a clear understanding of how you select participants for your survey research because it determines the population to which you may generalize your research findings. The accuracy and integrity of the overall survey research project are at risk if you perform poorly at the sampling stage of the research process. Thus, take note of the different types of probability and non-probability sampling techniques and how you conduct a simple random sampling technique. Sample.net provides other well-structured templates for survey reports and market research business plans