for Teachers for Schools for Enterprise
for Teachers for Schools for Enterprise
Course Navigator
Stratified Random Samples: Definition, Characteristics & ExamplesNext Lesson 

What is Random Sampling? - Definition, Conditions & Measures

Chapter 7 /  Lesson 2   Transcript
Try it risk-free for 30 days

An error occurred trying to load this video.

Try refreshing the page, or contact customer support.

Coming up next: Stratified Random Samples: Definition, Characteristics & Examples

You're on a roll. Keep up the good work!

Take Quiz Watch Next Lesson
 Replay
Your next lesson will play in 10 seconds
  • 0:01 Random Samples and Life
  • 0:41 What Are Random Samples?
  • 1:55 How Are Random Samples Used?
  • 4:40 Lesson Summary
Add to Add to Add to

Want to watch this again later?

Log in or sign up to add this lesson to a Custom Course.

Login or Sign up

Timeline
Autoplay
Autoplay
Speed

Recommended Lessons and Courses for You

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.

Random sampling is used in many research scenarios. In this lesson, you will learn how to use random sampling and find out the benefits and risks of using random samples.

Random Samples and Life

Stacy owns a cupcake shop. She is working on inventing new flavors that will encourage children to eat more vegetables. She is excited about unveiling her newest cupcake flavor: broccoli cupcakes. Stacy wants to taste test the cupcakes to see how children like the broccoli cupcakes. However, Stacy doesn't have the resources to give every child in the town a taste test. She can best learn how the children like her cupcakes by using random samples.

In this lesson, you will learn about random samples and how they are used in statistics.

What Are Random Samples?

Before using a random sample, Stacy needs to understand the definition of a random sample and the types of random samples that exist.

First, let's talk about populations. Populations are all members of a specified group. For example, if you wanted to learn about the average age of a person living in New Jersey, then everyone living in New Jersey would be your population for your experiment. When you conduct an experiment or gather data, you are trying to find out information on that population.

Second, you are probably collecting information from a sample. A sample is a part of a population used to describe the whole group. Since you often can't collect data on the entire population, you usually use a sample. This brings us to random samples, which are a sequence of equally distributed variables. Much of mathematics, especially statistics, is based on random sampling.

Some of the types of random sampling are:

  • Simple random samples
  • Stratified random samples
  • Cluster sampling

You will learn more about each of these types of sampling in other lessons.

How Are Random Samples Used?

Now that Stacy understands the definition and types of random samples, she needs to understand when to use random samples, how to select them, and the benefits and risks of random samples.

Random samples are best used to gather data about large populations. This is because you aren't likely to get an entire population to participate in a study.

Many times, there aren't enough resources to do this, or it is simply physically impossible to collect that much data. For example, Stacy probably doesn't have enough cupcakes for every child in the town, which is why she will use random samples instead. We can use random sampling to make observations about the entire population.

When you use random sampling, you want to make sure that you are giving all subsets, or all possible outcomes, equal probability. For example, rolling one 6-sided die is a random sample of what would happen if you rolled all of the 6-sided dies in the entire world. Since there are only six options, rolling one die gives all the outcomes equal probability.

In Stacy's case, there are many different possible outcomes in her population. She will want to include children in her sample that are of different ages, genders, and ethnicities to cover the population of her town. If she gave a taste test to just 10-year-old boys, then her sample would not give equal probability to all of the children in the town.

To unlock this lesson you must be a Study.com Member.
Create your account

Register to view this lesson

Are you a student or a teacher?

Unlock Your Education

See for yourself why 30 million people use Study.com

Become a Study.com member and start learning now.
Become a Member  Back
What teachers are saying about Study.com
Try it risk-free for 30 days
Description

Earning College Credit

Did you know… We have over 160 college courses that prepare you to earn credit by exam that is accepted by over 1,500 colleges and universities. You can test out of the first two years of college and save thousands off your degree. Anyone can earn credit-by-exam regardless of age or education level.

To learn more, visit our Earning Credit Page

Transferring credit to the school of your choice

Not sure what college you want to attend yet? Study.com has thousands of articles about every imaginable degree, area of study and career path that can help you find the school that's right for you.

Research Schools, Degrees & Careers

Get the unbiased info you need to find the right school.

Browse Articles By Category

Browse an area of study or degree level.

Recommended Articles
You are viewing lesson Lesson 2 in chapter 7 of the course:

 Back To Course

Statistics 101: Principles of Statistics

11 chapters | 144 lessons | 9 flashcard sets

Ch 7. Sampling
Ch 8. Regression &...

What is Random Sampling? - Definition, Conditions & Measures Related Study Materials

Create an account to start this course today
Try it risk-free for 30 days!
Create An Account

Explore our library of over 75,000 lessons

Browse by subject
Support