Random Sample in Psychology: Example & Definition

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  • 0:01 What Is a Random Sample?
  • 2:12 Advantages and Disadvantages
  • 2:54 Lesson Summary
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Lesson Transcript
Instructor: Yolanda Williams

Yolanda has taught college Psychology and Ethics, and has a doctorate of philosophy in counselor education and supervision.

A random sample is a very important component in research. In this lesson, learn more about random samples, some advantages and disadvantages of each, and look at some examples.

What is a Random Sample?

A random sample is a sample in which each member of the population has an equal chance of being selected to represent the whole.

In order for us to truly understand what a random sample is, we must first distinguish between a sample and a population. A population is all members of a defined group that have certain characteristics or attributes that we are interested in studying. Suppose we were interested in studying the sleep habits of college males in the United States. Our population would consist of all males who attend college in the U.S.

Since there are over 9 million men in this population, it would be virtually impossible for us to collect data from every single member. But how then do we collect our research data? We collect data from a sample, which is a portion of the population that's used to represent the entire population. In order to study our population, we can take 560 U.S. college males and collect data from them.

A sample allows us to collect data from a few members that represent the whole population. When a sample is truly representative of a population, we can make inferences that apply to the entire population. The best way to obtain a representative sample is through the use of a random sample.

In order for our sample to be random, two things must occur:

  1. Every member of the population must have an equal chance of being selected to be a part of the sample.
  2. The selection of one member of the population is not dependent upon the selection of another member.

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