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How to Use Sampling in Research


Before implementing a PR campaign, designing an ad, or even crafting messages for your business, research needs to be done about your target audience or who you are trying to reach. Without research, it would be difficult for a business to put out any kind of message since they need to know the audience and their opinions, traits, etc. (Here’s a great article on why research is important for your business.) One method when gathering data about a certain population is sampling. A sample is a portion of the population used to gather information about the larger population. Sampling is beneficial because sometimes it’s not feasible to survey or interview a large population of people. There are two broad types of sampling: probability and nonprobability. When defining these types it is important to know that your sample frame is a list of the items or people forming a population from which a sample is taken.

Probability Sampling (4 types)

-Simple Random Sample- This is when subjects are selected so that all members of the population have an equal opportunity to be selected. Individuals are chosen at random using a table of random numbers or lottery system. The advantages of this are it is easy to conduct, it is unbiased since it is chosen randomly, and it is representative of the population. A disadvantage is you have to have a complete list of the population.

-Systematic Sample- Systematic sampling involves a random start that is not at the beginning of the list and then proceeds with the selection of every kth element. An advantage of this type is the sample is easy to select. A disadvantage is it could be biased since some members of a population may be under or overrepresented.

-Stratified Random Sample- This is done by dividing the population into homogeneous sub-groups and then random samples are selected from each one. An advantage to this is it prevents and unrepresentative sample. A disadvantage is it may be difficult to decide how to divide the population.

-Cluster Sample- When using cluster sampling, the population is divided into homogeneous units, and then using similar techniques as simple random sampling, one of those units, or clusters, is chosen. An advantage of this is it is less expensive than other types of probability sampling. A disadvantage is it is the least representative type of sampling.

Still confused? Here are links to YouTube videos that explain each type visually! Simple Random Sample, Systematic Sample, Stratified Random Sample, and Cluster Sample

Non-Probability Sampling (3 Types)

-Convenience Sampling- Subjects are selected because they were easily accessible to the interviewer, not because they are representative of the population. For example, interviewing people you see walking around on a college campus. An advantage is it is convenient and easy. A disadvantage is it does not represent the entire population, so there can be bias.

-Purposive Sampling- Subjects are chosen based on who would be appropriate for the study. An advantage to this is it can be used to specifically reach groups who may be underrepresented. A disadvantage is since subjects are chosen specifically, the research can be biased.

-Snowball Sampling- Existing subjects are used to enlist more subjects. An advantage of this is it can allow access for hard to reach groups that a researcher would otherwise not be able to reach. A disadvantage would be it is not representative of the whole population.

Overall, there are many different ways to use sampling when conducting research! Each type has different advantages/ disadvantages and difficulty levels. Hopefully you can use this guide to help you decide how to use sampling during your research process!

Did our breakdown of these techniques help to decide what type of sampling to use should use when conducting research? Let us know in the comments below!

#tips #collegestudents #publicrelations #factchecking

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