Types and Examples of Sampling
What is sampling?
Sampling allows you to select individuals from a population and make statistical inferences about them. It also helps to estimate the characteristics of the entire population. Researchers in market research can use many sampling methods. This is because they don't have to survey the entire population in order to gain actionable insights.
It's also time-savings and economical and is the basis for any research design. A research survey software can use sampling techniques to optimize derivation.
If a drug company wants to investigate the adverse side effects of a drug in a country, it is nearly impossible to do a study that includes everyone. In this instance, the researcher selects a group of people from each demographic to conduct research and give feedback on drug behavior.
Types of sampling: sampling techniques
There are two types of sampling in market research: non-probability and probability sampling. Let's look closer at these two types of sampling.
Probability sampling: This is a method of randomly selecting members of a population from a group of people. This selection parameter gives all members equal opportunities to be part of the sample.
Non-probability Sampling: The researcher selects random members to conduct research. This sampling process is not pre-determined. This makes it hard for everyone to have equal opportunity to be part of a sample.
We will be discussing the different probability and nonprobability sampling techniques that you can use in any market research study.
Types of probability sampling illustrated with examples
Probability sampling is a method of selecting samples from larger populations using a theory-based sampling technique. This sampling method takes into account every member of the population, and forms samples using a fixed process.
If a population has 1000 members, each member has a chance of being chosen to be part of a sampling. Probability sampling reduces bias and gives every member a fair chance of being part of the sample.
Simple random sampling is one of most cost-effective sampling techniques. This reliable method allows you to obtain information from every individual in a population. Each person has the same chance of being selected to be part a sample.
In an example of this, 500 employees might prefer to eat chits instead of picking them out of a bowl if the HR department decides to organize team building activities. This would mean that each employee has an equal chance of being selected.
Cluster sampling: Researchers divide the population into sections, or clusters, which represent a population. A sample is created by identifying clusters based on demographic parameters, such as location, age, sex, and gender. This makes it easy for survey designers to infer useful information from the feedback.
The United States can, for example, divide the results into clusters based in states such as California and Texas. This will make it easier to conduct a survey. The results will be organized in states and will provide valuable information about immigration.
Systematic sampling is a method that allows researchers to randomly select members of a population. It involves the selection of a starting place for the sample and the selection of a sample size that can easily be repeated at regular intervals. This type of sampling has a predefined range and is therefore the quickest.
One example is that a researcher wants to collect a systematic sample from 500 people within a population size of 5000. He/she will number each element of a population between 1-5000 and choose every 10th person to be part of the sample. Total population/Sample size = 5000/500 = 10.
Stratified random sample: Stratified sampling is a method that divides the population into smaller, more representative groups. Each group can be organized to allow for sampling.
Researcher looking at the characteristics of people from different income levels will create strata according to their annual family income. Eg., less than $20,000; $21,000 – $30,000; $31,000 – $40,000; $41,000 – $50,000, etc. This allows the researcher to determine the characteristics and income levels of the people. Marketers can identify which income groups to target, and which to eliminate in order to build a plan that yields results. Inherited Randomly Selected Numbers From a Larger Collection of Base Numerals
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