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Simple Random Samples: Definition & Examples

Simple Random Samples: Definition & Examples
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  • 0:01 Simple Random Sampling
  • 2:54 Using Simple Random Sampling
  • 4:03 Lesson Summary
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Lesson Transcript
Instructor: Cathryn Jackson

Cat has taught a variety of subjects, including communications, mathematics, and technology. Cat has a master's degree in education and is currently working on her Ph.D.

Simple random sampling is a common method used to collect data in many different fields. From psychology to economics, simple random sampling can be the most feasible way to get information. Learn all about it in this lesson!

Simple Random Sampling

Adrian is gathering information for a trip he plans to take. He is thinking about moving permanently to a new town. However, he wants to get an idea of how the people in the town feel about the safety of the town. Unfortunately, Adrian does not have the resources to ask every person in the town how they feel about the safety. How should Adrian go about collecting this data?

In this lesson, you will learn about how to use and recognize simple random sampling in statistics. First, let's discuss the meaning of simple random sampling by defining a few key terms.

When you are doing an experiment, you want to gather information about a population. A population is all members of a specific group. For example, the population of Adrian's research will be, quite literally, the population of the town. Sometimes a population is not that geographically contained. If Adrian wanted to know the typical income of a person over 30, then anyone with a job over 30 in the entire world would be in his population. Since Adrian does not have the resources to ask everyone in the town how they feel about safety, he will have to use a sample of the population.

A sample is a part of the population used to describe the whole group. Adrian will want to make sure all demographics are represented in his sample. He doesn't just want the opinion of the teenagers in his town or just the men over 50. He wants to get all demographics equally represented in his sample. To do this, Adrian will need to use random sampling, which is a method of choosing an equally distributed subset from a larger population. This takes us to simple random sampling or SRS, which is a type of random sampling where the variables have an equal and unsystematic chance of selection.

For example, if you were to toss a handful of 6-sided dice on a table, you would have an equal and unsystematic likelihood of getting a one, two, three, four, five, or six. When I say unsystematic, I mean you aren't throwing the dice and then only choosing the number off of every other dice on the table. When you use a system to randomize the selection instead of just taking the random selections as they fall, then you are not using simple random selection.

In Adrian's experiment, Adrian can use a phone book with all of the names of the people in the town as his population group. He can then put each name on a piece of paper and put the papers into a bag. Adrian can blindly select a certain number of names from the bag as part of his simple random sampling.

Now that you understand the meaning of simple random sampling, let's discuss how to use simple random sampling.

Using Simple Random Sampling

Simple random sampling is meant to be a balanced representation of the demographics of the population. When you are discussing a population of people, that means all of the demographics: age, race, religion, ethnicity, socioeconomic status, education level, etc. that are all currently present in the given population.

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