Skip Nav
#
Types of Sampling Methods and Techniques in Research

##
Additional Resources

## Navigation menu

❶If we tag and release the fish we caught, we can see whether we have caught a particular fish before.
## Selecting Target Population

## Main Topics

### Privacy Policy

### Privacy FAQs

### About Our Ads

### Cookie Info

Determining the right kind and number of participants in a sample group, also known as sampling, is one of the basic steps in conducting surveys. Before you can be able to have a sample for your survey, you need to define your target population first. If your survey goal is to know the effectiveness of a product or service, then the target population should be the customers who have utilized it. It is critical to select the most appropriate target population in order to satisfy the purpose of executing the survey.

There are numerous ways of getting a sample, but here are the most commonly used sampling methods:. The purest form of sampling under the probability approach, random sampling provides equal chances of being picked for each member of the target population. Examples of stratum include mothers, fathers, students, teachers, females, males, etc. Sampling error is usually lower in stratified sampling than in random sampling.

In systematic sampling , every Nth name is selected from the list of the members of the target population. For instance, the sample will include the participants listed in every 10th from the list. That means the 10th, 20th, 30th and so on will be selected to become the members of the sample group. This non-probability sampling method is used when there are only a few available members of the target population who can become the participants in the survey.

Another non-probability method, quota sampling also identifies strata like stratified sampling, but it also uses a convenience sampling approach as the researcher will be the one to choose the necessary number of participants per stratum.

As the name suggests, purposive sampling means the researcher selects participants according to the criteria he has set. This is called sampling. The group from which the data is drawn is a representative sample of the population the results of the study can be generalized to the population as a whole. The sample will be representative of the population if the researcher uses a random selection procedure to choose participants.

The group of units or individuals who have a legitimate chance of being selected are sometimes referred to as the sampling frame. If a researcher studied developmental milestones of preschool children and target licensed preschools to collect the data, the sampling frame would be all preschool aged children in those preschools.

Students in those preschools could then be selected at random through a systematic method to participate in the study. This does, however, lead to a discussion of biases in research. For example, low-income children may be less likely to be enrolled in preschool and therefore, may be excluded from the study.

Extra care has to be taken to control biases when determining sampling techniques. There are two main types of sampling: The difference between the two types is whether or not the sampling selection involves randomization. Randomization occurs when all members of the sampling frame have an equal opportunity of being selected for the study. Following is a discussion of probability and non-probability sampling and the different types of each.

Probability Sampling — Uses randomization and takes steps to ensure all members of a population have a chance of being selected. There are several variations on this type of sampling and following is a list of ways probability sampling may occur:. It is also the most popular way of a selecting a sample because it creates samples that are very highly representative of the population. Simple random is a fully random technique of selecting subjects. All you need to do as a researcher is ensure that all the individuals of the population are on the list and after that randomly select the needed number of subjects.

This process provides very reasonable judgment as you exclude the units coming consecutively. Simple random sampling avoids the issue of consecutive data to occur simultaneously.

Then the researcher randomly selects the final items proportionally from the different strata. It means the stratified sampling method is very appropriate when the population is heterogeneous. Stratified sampling is a valuable type of sampling methods because it captures key population characteristics in the sample. In addition, stratified sampling design leads to increased statistical efficiency. Thus, with the same size of the sample, greater accuracy can be obtained.

This method is appropriate if we have a complete list of sampling subjects arranged in some systematic order such as geographical and alphabetical order. The process of systematic sampling design generally includes first selecting a starting point in the population and then performing subsequent observations by using a constant interval between samples taken. This interval, known as the sampling interval, is calculated by dividing the entire population size by the desired sample size.

For example, if you as a researcher want to create a systematic sample of workers at a corporation with a population of , you would choose every 10th individual from the list of all workers. This is one of the popular types of sampling methods that randomly select members from a list which is too large. A typical example is when a researcher wants to choose individuals from the entire population of the U. It is impossible to get the complete list of every individual. So, the researcher randomly selects areas such as cities and randomly selects from within those boundaries.

Cluster sampling design is used when natural groups occur in a population. The entire population is subdivided into clusters groups and random samples are then gathered from each group.

Cluster sampling is a very typical method for market research. The cluster sampling requires heterogeneity in the clusters and homogeneity between them. Each cluster must be a small representation of the whole population. The key difference between non-probability and probability sampling is that the first one does not include random selection. Non-probability sampling is a group of sampling techniques where the samples are collected in a way that does not give all the units in the population equal chances of being selected.

Probability sampling does not involve random selection at all. Most commonly, the units in a non-probability sample are selected on the basis of their accessibility.

They can be also selected by the purposive personal judgment of you as a researcher. Types of Non-Probability Sampling Methods. There are many types of non-probability sampling techniques and designs, but here we will list some of the most popular. As the name suggests, this method involves collecting units that are the easiest to access: It forms an accidental sample.

There are many methods of sampling when doing research. This guide can help you choose which method to use. Simple random sampling is the ideal, but researchers seldom have the luxury of time or money to access the whole population, so many compromises often have to be made.

Sampling and types of sampling methods commonly used in quantitative research are discussed in the following module. Learning Objectives: Define sampling and randomization. Explain probability and non-probability sampling and describes the different types of each.

Sampling Methods can be classified into one of two categories: Probability Sampling: Sample has a known probability of being selected. Non-probability Sampling: Sample does not have known probability of being selected as in convenience or voluntary response surveys. RESEARCH METHOD - SAMPLING 1. Sampling Techniques & Samples Types. 2. Outlines Sample definition Purpose of sampling Stages in the selection of 3. The process of selecting a number of individuals for a study in such a way 6. Population the larger group from which individuals are selected to participate in a study.

Types of Sampling Methods and Techniques in Research The main goal of any marketing or statistical research is to provide quality results that are a reliable basis for decision-making. That is why the different types of sampling methods and techniques have a crucial role in research methodology and statistics. Video: What is Sampling in Research? - Definition, Methods & Importance - Definition, Methods & Importance The sample of a study can have a profound impact on the outcome of a study.