Sampling Methods

Watch the Video 

The text below is similar to what is said in the video. But if you would like to read about these sampling methods and their advantages and disadvantages, the information is here.

Once you understand the different sampling methods, please choose one to use for your survey and send it out!

Be prepared to explain the sampling method used and how it worked in the next path!

Vocabulary

  • Survey: a document that contains a series of questions used to collect data for a specific purpose. 
  • Sampling is the technique where a small group or a sample of the population is selected for primary research.

Quota Sampling: When a certain number of people from different segments of the population are sampled. 

An example of quota sampling in a community project about recycling habits would be to gather information from different age groups in their community. They would need to break it down into children, teenagers, adults and seniors. 

To do this using quota sampling, they might first decide on the quotas for each group. For example, aiming for 20% children (ages 7-12), 30% teenagers (ages 13-19), 30% adults (ages 20-60), and 20% seniors (ages 61 and above). If you would like to have 60 people take your survey, then you need 12 children, 18 teenagers, 18 adults and 12 seniors. 

Then go and recruit participants until these quotas are reached. Schools, community centers, retirement homes, parents work places, would all be good places to find different age groups to reach these quotas. 

This method ensures that there is a sample that reflects the different age demographics of their community. 

There are other ways to segment a group: gender, geography, socio-economic. Decide what data the survey is gathering and find the groups that make the most sense to gain insight into your questions.

Random Sampling: This method of sampling gives everyone in the population an equal chance of being selected. 

Define the population. It could be the number of kids in your high school or class. 

Calculate how many are in the population that you would like to sample. You could ask the administration for an accurate list of students. Remember, a good sample size is about 10% of the population. 

Assign numbers to the students in the school. Using a random number generator or a similar method, it would randomly select a subset of the population. Each person in the population should have an equal chance of being selected.

Analysis: After collecting the survey responses, the data can be analyzed to draw conclusions about the topics being investigated, such as attitudes towards school policies, favorite subjects, extracurricular activities, etc.

By using random sampling within a school, it can be ensured that their survey results are more likely to be representative of the entire student body. This method helps to minimize biases that could arise if they were to select students based on convenience or other non-random methods.

Convenience Sampling: this uses the people that are easiest to sample. 

Identify the most accessible group of respondents that need to answer the survey. If it is in a school, it could be the students in their own grade. If it is in the community, it could be the people that live closest.  

Select participants based on convenience. Ask the people that are closest to you to answer the survey. Again, remember that 10% of the population is a good number to shoot for. 

While convenience sampling might be quicker and more straightforward to implement compared to random sampling, it’s essential to acknowledge its limitations. The sample obtained through convenience sampling may not be representative of the entire student population, as it relies on the availability and willingness of participants. Therefore, the findings may not give a good understanding of the entire school.

Snowball sampling: is when you ask a few people you know to help you find more people for a survey or study. Then, those new people find even more people, and it keeps going like a snowball rolling downhill, getting bigger and bigger.

Start by selecting a few initial participants from their network based on the population that data will be collected from. 

After collecting data from these initial participants, they would ask them to refer more participants they know who might be interested in participating in the survey. These referred participants become the next wave of participants.

Expansion: The process continues, with each new participant referring additional participants. This “snowball effect” helps to expand the sample size rapidly.

Snowball sampling is particularly useful when traditional sampling methods like random or convenience sampling are impractical or ineffective, such as when the population is highly interconnected or when it’s difficult to identify and access potential participants. However, it’s essential to be aware of potential biases introduced by relying on referrals and to interpret the findings with caution, as the sample may not be fully representative of the entire population.

To continue, return to Module 3 Opportunity Card.

This Collective


By MissAmy

Guanacaste, Costa Rica


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