Sampling Methods

Sampling Methods: Types with Examples
Sampling Methods
Sampling is an essential part of any research project. The right sampling method can
make or break the validity of your research, and it’s essential to choose the right method
for your specific question. In this article, we’ll take a closer look at some of the most
popular sampling methods and provide real-world examples of how they can be used to
gather accurate and reliable data.
From simple random sampling to complex stratified sampling, we’ll explore each
method’s pros, cons, and best practices. So, whether you’re a seasoned researcher or just
starting your journey, this article is a must-read for anyone looking to master sampling
methods. Let’s get started!
What is sampling?
Sampling is a technique of selecting individual members or a subset of the
population to make statistical inferences from them and estimate the characteristics of the
whole population. Different sampling methods are widely used by researchers in market
research so that they do not need to research the entire population to collect actionable
insights.
It is also a time-convenient and cost-effective method and hence forms the basis of
any research design. Sampling techniques can be used in research survey software for
optimum derivation.
For example, suppose a drug manufacturer would like to research the adverse side
effects of a drug on the country’s population. In that case, it is almost impossible to
conduct a research study that involves everyone. In this case, the researcher decides on a
sample of people from each demographic and then researches them, giving him/her
indicative feedback on the drug’s behavior.
Types of sampling: sampling methods
Sampling in market action research is of two types – probability sampling and non-
probability sampling. Let’s take a closer look at these two methods of sampling.
Probability sampling: Probability sampling is a sampling technique where a
researcher selects a few criteria and chooses members of a population randomly. All the
members have an equal opportunity to participate in the sample with this selection
parameter.
Non-probability sampling: In non-probability sampling, the researcher randomly
chooses members for research. This sampling method is not a fixed or predefined selection
process. This makes it difficult for all population elements to have equal opportunities to be
included in a sample.
Types of probability sampling with examples:
Probability sampling is a technique in which researchers choose samples from a
larger population based on the theory of probability. This sampling method considers every
member of the population and forms samples based on a fixed process.
For example, in a population of 1000 members, every member will have a 1/1000
chance of being selected to be a part of a sample. Probability sampling eliminates sampling
bias in the population and allows all members to be included in the sample.
Types of probability sampling with examples:
Probability sampling is a technique in which researchers choose samples from a larger
population based on the theory of probability. This sampling method considers every
member of the population and forms samples based on a fixed process.
For example, in a population of 1000 members, every member will have a 1/1000
chance of being selected to be a part of a sample. Probability sampling eliminates sampling
bias in the population and allows all members to be included in the sample.
Uses of probability sampling
Reduce Sample Bias: Using the probability sampling method, the bias in the sample
derived from a population is negligible to non-existent. The sample selection mainly depicts
the researcher’s understanding and inference. Probability sampling leads to higher-quality
data collection as the sample appropriately represents the population.
Diverse Population: When the population is vast and diverse, it is essential to have
adequate representation so that the data is not skewed toward one demographic. For
example, suppose Square would like to understand the people that could make their point-
of-sale devices. In that case, a survey conducted from a sample of people across the US
from different industries and socio-economic backgrounds helps.
Create an Accurate Sample: Probability sampling helps the researchers plan and
create an accurate sample. This helps to obtain well-defined data.
Types of non-probability sampling with examples
The non-probability method is a sampling method that involves a collection of
feedback based on a researcher or statistician’s sample selection capabilities and not on a
fixed selection process. In most situations, the output of a survey conducted with a non-
probable sample leads to skewed results, which may not represent the desired target
population. But, there are situations, such as the preliminary stages of research or cost
constraints for conducting research, where non-probability sampling will be much more
useful than the other type.
Four types of non-probability sampling explain the purpose of this sampling method
in a better manner:
Convenience sampling: This method depends on the ease of access to subjects such
as surveying customers at a mall or passers-by on a busy street. It is usually termed as
convenience sampling because of the researcher’s ease of carrying it out and getting in
touch with the subjects. Researchers have nearly no authority to select the sample
elements, and it’s purely done based on proximity and not representativeness. This non-
probability sampling method is used when there are time and cost limitations in collecting
feedback. In situations with resource limitations, such as the initial stages of research,
convenience sampling is used.
Judgmental or purposive sampling: Judgmental or purposive samples are formed
at the researcher’s discretion. Researchers purely consider the purpose of the study, along
with the understanding of the target audience. For instance, when researchers want to
understand the thought process of people interested in studying for their master’s degree.
The selection criteria will be: “Are you interested in doing your masters in …?” and those
who respond with a “No” are excluded from the sample.
Snowball sampling: Snowball sampling is a sampling method that researchers apply
when the subjects are difficult to trace.
Quota sampling: In Quota sampling, members in this sampling technique selection
happens based on a pre-set standard. In this case, as a sample is formed based on specific
attributes, the created sample will have the same qualities found in the total population. It
is a rapid method of collecting samples.

Sampling Methods

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Sampling Methods: Types with Examples

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