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Samples & Populations in Research: Definition

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  • 0:07 Participants
  • 0:46 Population
  • 1:36 Sample
  • 4:15 Represent
  • 5:06 Lesson Summary
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Lesson Transcript
Instructor
Devin Kowalczyk

Devin has taught psychology and has a master's degree in clinical forensic psychology. He is working on his PhD.

Expert Contributor
Maria Airth

Maria has a Doctorate of Education and over 20 years of experience teaching psychology and math related courses at the university level.

When planning an experiment, you will likely use groups of participants. This lesson explores the types of groups an experimenter can collect data from and the reason why there are different groups.

Participants

When you conduct an experiment or survey you collect information from a group of people. Now, while 'group of people' may seem like an adequate description, it is, in fact, not. We need more a specific term because the statistics we use are different depending on group we use. But don't worry, there's no complicated process to identifying the group of people you use.

The first group of people is a population, which is defined as the complete collection to be studied. The second group is a sample, which is defined as a section of the population. Let's look at some examples to help make this a little clearer.

Population

When you are attempting to study a population, you have to collect information from everyone in that group. This makes it extremely difficult to study populations. For example, imagine if you are going to study:

  • All people with schizophrenia in the United States (approximately 3.1 million individuals).
  • Californians' view on raisins (38 million).
  • Immigrants beliefs about the U.S.'s foreign policy (nobody really knows how many if you include illegal and legal).

So you can see the difficulty with studying populations. Smaller populations, like community colleges, are easier to collect population data. However, the issue here is if you have one person who fails to contribute, then you don't have a population.

Sample

Most social researchers realize that obtaining information from every person in a population is next to impossible. So instead of trying to collect everyone's information, they collect a sample of the population. But unlike a population, which is everyone, there are different ways you can collect a sample of a population. The different ways of taking a sample are sort of like how there are different ways to cut a cake. Here is a list of the different sampling techniques:

  • Random sample: each individual in the population has an equal chance of being selected.
  • Stratified sample: a researcher divides the population into groups based on characteristics, and then the researcher randomly selects from each group based on its size.
  • Quota sample: a researcher deliberately sets a requirement to ensure a particular group is represented.
  • Purposive sample: a researcher purposefully focuses on a particular subset of a population.
  • Convenience sample: selection of the sample is based on ease of accessibility.

So, enough talking about cake; what would these samples look like if they were real scientific studies? Let's say you're interested in studying people with schizophrenia in the United States.

A random sample would mean that each person with schizophrenia has an equal chance of being part of your study. This might mean a lot of travel since the U.S. is a big place.

A stratified sample would be useful if you were interested in looking at a particular subset of people with schizophrenia. What if you were interested in comparing the level of symptoms between upper socioeconomic status and lower socioeconomic status?

A quota sample might be useful if you were interested in how culture impacts schizophrenia. So you may set a requirement that certain percentages of your group are Native American, African American, Mexican American, Asian American, and European American.

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Additional Activities

When to Use Population and Sample Examples

This activity will allow learners to choose the correct style of participant selection through the use of open-ended scenario examples.

Materials

  • List of research scenarios, such as:
    • A researcher wants to study the remaining white rhinoceroses in Africa.
    • A school is interested in understanding more about how students interact with each other. They want to compare age groups.
    • A student wants to conduct a survey among his friends on social media.
  • Make sure you have at least 2 examples of each type of sample and 2 examples that relate to the population.

Instructions

  • Divide your class into small groups of 2-4.
    • It is okay for students to work independently if necessary.
  • Tell your students that you will read a scenario and they must decide on whether the research scenario relates to a population or a sample. If it is a sample, they must identify the type of sample needed.
  • Read the first scenario. Give students a minute or two to decide on an answer.
  • Choose a group to answer. Instruct the group to give their answer as well as justification for the answer.
    • Before moving on, ask if any groups chose a different answer. Allow those groups to justify their answers.
  • If a student is working independently (as in a homeschooling environment), allow the student to answer and explain his/her answer after each scenario.
    • Ask the student to consider how to change the scenario to allow it to fit a different sample type.
  • Continue until you have read all scenarios.

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