Sampling Methods: Examples and Uses

Researchers often use different ones in market research Sampling methods, so they don't have to survey the entire population to gain actionable insights.

Today we will look at the characteristics of each of these methods so that you can decide which one you need to carry out to make your research project a success.

Definition of samples

Sampling is a technique for selecting individual members or a subset of the population to draw statistical conclusions and estimate the characteristics of the entire population.

It is also a time and cost efficient method and therefore forms the basis of any research design. Sampling techniques can be used in a research survey software program to derive optimal results.

For example, if a drug manufacturer wants to study the adverse side effects of a drug in a country's population, it is almost impossible to conduct a research study in which all people participate. In this case, the researcher selects a sample of people from each demographic group, which he then studies to give them indicative feedback on the drug's behavior.

Sampling methods

There are two sampling methods: probability sampling and non-probability sampling:

Probability sampling: Probability sampling is a sampling technique in which a researcher makes a selection based on some criteria and randomly selects members of a population. With this selection parameter, all members have an equal chance of being part of the sample.

Non-probability sampling: In non-probability sampling, the researcher randomly selects the members of the research population. This sampling method is not a fixed or predefined selection process. This makes it difficult for all elements of a population to have an equal chance of being included in a sample.

Examples of sampling methods

Below we will learn about different types of samples that can be used in any market research study.

Probability sampling is a sampling technique in which researchers select samples from a larger population using a method based on probability theory. This is one of the sampling methods in which all members of the population are taken into account and the samples are formed based on a specified process.

For example, in a population of 1000 members, each member has a 1/1000 chance of being included in a sample. Probability sampling eliminates bias in the population and gives all members a fair chance of being included in the sample.

There are four types of sampling methods:

Simple random sampling

One of the best probability sampling methods that helps save time and resources is the simple sampling method. It is a reliable method of obtaining information in which each member of a population is randomly selected. Every person has an equal chance of being included in the sample.

For example, in a company with 500 employees, if the HR department decides to implement team-building activities, it is very likely that they would prefer to draw tokens from a bowl. In this case, each of the 500 employees has an equal chance of being selected.

Cluster sampling

In this method, also known as cluster sampling, researchers divide the entire population into sections or clusters that represent a population. The clusters are identified and sampled based on demographic parameters such as age, gender, location, etc. This makes it very easy for the survey creator to draw effective conclusions from the feedback.

For example, if the US government wants to determine the number of immigrants living in the United States, it can divide them into groups based on states such as California, Texas, Florida, Massachusetts, Colorado, Hawaii, etc. This type of survey is more effective because the results are organized by state and provide objective immigration data.

Systematic sampling methods

Researchers use the systematic sampling method to draw samples from a population at regular intervals.

To do this, a starting point for the sample and a sample size must be determined, which can be repeated at regular intervals. These types of sampling methods have a predefined scope and are therefore the least time consuming.

For example, a researcher intends to collect a systematic sample of 500 people from a population of 5000 people. He/she numbers each element of the population from 1 to 5000 and selects every tenth person for the sample (population/sample size = 5000/500 = 10).

Stratified samples

In stratified random sampling, the researcher divides the population into smaller groups that do not overlap but represent the entire population. During sampling, these groups can be organized and a separate sample can then be drawn from each group.

For example, a researcher who wants to analyse the characteristics of people belonging to different annual income groups would create strata (groups) according to annual household income.

For example, less than $20.000, $21.000 to $30.000, $31.000 to $40.000, $41.000 to $50.000 and so on.

From this, the researcher draws conclusions about the characteristics of people belonging to different income groups. The marketers can analyse which income groups they should target and which they should exclude to achieve the desired results.

Uses of Probability Sampling

Probability sampling can be used in a variety of ways:

• Reducing sample bias: When using probability sampling techniques, the bias of the sample derived from the population is negligible or non-existent, allowing higher quality data to be collected as the sample adequately represents the population.
• Diverse population: When the population is large and diverse, it is important to have adequate representation so that the data is not biased towards a single demographic group.
• Creating an accurate sample: Probability sampling helps researchers plan and create an accurate sample. This helps in obtaining well-defined data.

Types of non-probability sampling and examples

Non-probability sampling is one of the sampling methods in which information is collected based on a researcher or statistician's ability to select samples rather than on the basis of a fixed selection procedure.

In most cases, the result of a survey conducted with a non-probability sample will produce biased results that may not represent the desired target population. However, there are situations, e.g. B. in advance of research or when conducting research for cost reasons, in which non-probability sampling is much more useful than the other types.

These four types of sampling methods best explain the purpose of these sampling methods:

Convenience sampling

This method is based on easy access to the subjects, such as: B. a survey of customers in a shopping center or of passers-by on a busy street.

It is often referred to as random sampling because it is easy for the researcher to conduct it and contact the subjects. Researchers have virtually no power to select sample elements, and selection is based solely on proximity rather than representativeness.

This type of sampling method is used when there are time and cost constraints in collecting information. In situations where resource constraints exist, such as: B. in the initial phase of research, random samples are used.

For example, startups and non-governmental organizations often conduct random sampling in a mall to distribute flyers for upcoming events or a specific cause by standing at the mall entrance and randomly handing out flyers.

Purposive, Judgmental or Critical Sampling

Judgmental samples are formed at the discretion of the researcher. Researchers only consider the purpose of the study and understanding of the target audience.

For example, when researchers want to understand the thought process of people interested in pursuing a master's degree. The selection criteria will then be: “Are you interested in doing your Masters in…?”, and those who answer “No” will be excluded from the sample.

Ponzi scheme

The pyramid scheme is one of the sampling methods that researchers use when the subjects are difficult to identify.

For example, it will be extremely difficult to interview unhoused people or illegal immigrants. In such cases, researchers can use snowballing to identify a few categories that they can survey to obtain results.

Researchers also use this sampling method in situations where the topic is very sensitive and not openly discussed, such as: B. in surveys to collect information about HIV and AIDS. Not many victims will answer the questions willingly. However, researchers can reach out to people they may know or volunteers connected to the subject to find victims and gather information.

Quota sampling

The selection of members in this sampling technique is done based on a predetermined rule. Since the sample in this case is formed based on certain characteristics, the sample has the same properties as the population. It is a quick sampling method.

Uses of non-probability sampling

Non-probability sampling is used for the following purposes:

• Creation of a hypothesis: Researchers use non-probability sampling to create a hypothesis when there is little or no prior information. This method helps in immediate return of data and provides a foundation for future research.
• Exploratory research: This sampling technique is commonly used by researchers when conducting qualitative research, pilot studies, or exploratory research.
• Budget and time constraints: Used when budget and time constraints exist and some preliminary data needs to be collected. Since the survey design is not rigid, it is easier to randomly select respondents and have them complete the survey or questionnaire.

How do you decide which sampling methods to use?

For any research paper, it is important to choose a sampling method that is precisely tailored to the objectives of your study. The effectiveness of your sampling depends on several factors.

Below are some steps that experienced researchers follow to decide on the best sampling method.

• Write down the objectives of the research. Generally, this should be a combination of cost, precision, or accuracy.
• Identify effective sampling techniques that can potentially achieve the research objectives.
• Test each of these methods and see if they help achieve the goal.
• Choose the method that is most suitable for the examination.

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KEYWORDS OF THIS BLOG POST

Sampling methods | sample | Method