Sampling Methods


A Quick Review:

What is a sample?

A sample is a small group that is selected from a population. This group typically represent a population.

Why do we need to take samples from the population?

We need to take samples because the population is typically too large to study. If we are trying to do an experiment on teen Snapchat users, it would be impossible to include teen Snapchat user in this study. Therefore, we would have to use a group of teen Snapchat users to represent all of the teen snapchat users.

Sampling Methods:

Random Sampling:

  • Random sampling is when everyone in the population has an equal chance of being chosen.
  • In random sampling, the sampling is completely random and there is no rhyme or reason.
  • Rolling a fair dice, flipping a fair coin, pulling names out of a hat, using a random number generator, and using a random number table are all examples of a random sample.
  • Example of a random sample: It seems as though every other student but you has a dog. You want to survey the entire school, but there is just too many people. So you assign everyone in your school a number and then pull 400 names out of a hat. You then use this group of 400 as a representative of your school.


Systematic Sampling:

  • Systematic sampling is when every person or thing in the population is assigned a number. A random starting point is then chosen and every nth person is chosen.
  • Phrases, such as “every 10th person” or “every 4th person,” indicated systematic sampling.
  • Example of a systematic sample: You want to know what proportion of the boys at your school are fuckboys. You can’t sample the entire school. You use an alphabetical list of everybody in your school. First you choose 3 as the starting point and then you include every 10th subject in your sample.


Stratified Sampling:

  • Stratified sampling is when the population is divided into groups and random intact groups are chosen to represent the population.
  • Phrases, such as “10 people from each group were chosen,” indicated stratified sampling.
  • Example of stratified sampling: You are the student class president and you want to better your school. At your school there are 5 groups: the jocks, the nerds, the stoners, the geeks, and the mean girls. You want to get equal representation of each group, so you randomly select 5 representatives from each group to represent the school.


Clustered Sampling:

  • Clustered sampling is when intact/whole groups are chosen for a sample.
  • Phrases, such as “all of Thomas Johnson High School” or “all of 3rd block algebra 2,” indicate clustered sampling.
  • Example of clustered sampling: You want to represent all of the schools in your county in a sample. You randomly select 2 schools from the county to represent all of the schools in your county.

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