Convenience Sample: Example & Definition

Sampling Defined

Let's say you are interested in the effects of caffeine on study habits. To be able to say with absolute confidence that caffeine influences a study habit, you would have to test everyone in the entire world. That is going to be difficult, since you don't have a huge government grant. In fact, you don't have any real money to conduct a large research experiment. One option is to use a convenience sample.

A population is all of the people who could possibly be in your study. If your population is humans, then it is comprised of the seven billion people on the Earth. If your population is City A, then it is all people who live in City A.

A sample is a small set of a population that is used to draw conclusions about the bigger group. This allows you to run smaller experiments and then use statistics to draw conclusions about the population, saving you time and money, since you did not have to test the whole population. So, instead of experimenting on seven billion humans, you can test a few people from every country. Instead of interviewing all of City A, you test a few hundred from different neighborhoods in City A.

A sample focuses on how representative of the population it is, or how well your sample is like the population. A few people from many different countries could be very representative of the world's population. A group of people from a different City B would not be a good representation of City A.

Convenience sampling is a sample taken from a group you have easy access to. The idea is that anything learned from this study will be applicable to the larger population. By using a large, convenient size, you are able to more confidently say the sample represents the population.

Furthermore, the convenient group you are testing should not be fundamentally different than if you had taken a sample from another area. If you are trying to say something about women, for example, then your convenient sample cannot be men.

Example

You are still interested in the effects of caffeine on study habits of college students. To test the whole population, you would need all current college students and a whole lot of time and soda. A sample would be a test of a few college students from all of the colleges in the U.S., requiring you to fly them in for the testing.

A convenience sample would be a large group of college students from your local college or colleges. They are close by, are in college, and are not different from other college students.

Limitations

The obvious limitation of a convenience sample is it may not be representative of the population. In our example, a group of college students who attend Harvard are different than those who attend community college. Differences between a community college student could be age (those starting at community college versus those finishing Harvard), prior study habits, socioeconomic status, and familiarity with a subject. These differences could cause an experiment to no longer be useful.

One way to reduce this limitation is to use a large group. When using statistics on a sample, the rule is more is better. If you have more participants, then your sample is more representative of the population.