Non-Probability Sampling Methods: Definition & Types

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• 0:05 Non-Probability Sampling
• 1:08 Convenience
• 2:44 Quota
• 4:30 Judgmental
• 6:05 Lesson Summary

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Lesson Transcript
Instructor: Natalie Boyd

Natalie is a teacher and holds an MA in English Education and is in progress on her PhD in psychology.

There are many different ways to choose a sample for a research study. In this lesson, we'll look at three types of non-probability sampling: convenience, quota, and judgmental (or purposive sampling) and when to use each type.

Non-Probability Sampling

Kiera is a psychologist. She's interested in studying why people believe the way they do about the death penalty. She puts together a survey asking people for reasons to support their side of the capital punishment debate.

But who should Kiera give the survey to? She wants her research to say something about adults over age 18 in the United States, but it wouldn't be possible for her to give the survey to every American adult. That would take forever!

So, Kiera needs to develop a sample, or group of subjects. This is done through a process called sampling. The goal is to choose a sample that represents the whole population so that Kiera can make inferences about the population from her sample.

One major category of sampling techniques is called non-probability sampling. In non-probability sampling, subjects are chosen to be part of the sample in non-random ways. Let's look closer at three non-probability sampling methods - convenience, quota, and judgmental sampling.

Convenience

OK, so Kiera wants to give her survey to a sample of people in order to learn why Americans feel the way they do about capital punishment. She and her two research assistants go to a shopping mall on a Tuesday morning and stop people to ask their opinion on the death penalty and why they feel that way.

Kiera is using the convenience sampling method, which is just what it sounds like: a researcher selects the sample based on convenience. The subjects selected to be part of the study's sample are there and are available to be tested.

Convenience sampling has a major problem: the people who are readily available are not necessarily representative of the population at large. Think about Kiera's study; if she and her research assistants poll the people at a shopping mall on a Tuesday morning, their sample is limited to subjects who are at a shopping mall on a Tuesday morning. Anyone with a nine-to-five job (which includes most adults in America) will be at work, not at the mall, which means that they won't be part of Kiera's sample. That's a problem!

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