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Writer's pictureKristin Williams

A Sampling of Samples: Random vs. Convenient

In scientific studies, random sampling is the gold standard. By ensuring that everyone has an equal chance of being selected, researchers get a truly representative snapshot of the population. But when it comes to community engagement, the dream of random sampling often runs into hard realities.


Why Random Sampling Doesn’t Work in Community Engagement

Random sampling in community engagement would require having an up-to-date list of every resident’s contact info—something that simply doesn’t exist. Instead, we usually work with what's available: email lists, social media followers, or public meeting attendees. Unfortunately, these groups often consist of those already engaged and aware, not a true cross-section of the community. This approach is known as a convenience sample because it’s based on who’s easy to reach rather than a truly random selection.


Watch Out for “Random Sample” Guarantees

Be cautious if a consultant or company promises a “random sample” for a community survey. Often, they’re offering a random draw from a convenience sample—like an email list—not a genuine random sample. Ask how they have a list of everyone in your community from which they could pull a random sample. If they can’t explain or claim it’s proprietary, that’s a big red flag. Any reputable group will be transparent about their methods. Just remember: a random list pulled from a convenience sample is still a convenience sample.


Convenience Samples Can Still Be Useful

Convenience samples aren't all bad– they can still provide valuable insights when used thoughtfully and transparently. In community engagement, convenience samples are about reaching as many people as possible with available resources, offering a broad look at community sentiment. By being open about the limitations, we avoid overstating the data’s representativeness and make informed decisions based on what we know, while identifying areas for deeper outreach. Used well, convenience samples lay a solid foundation for inclusive engagement that can grow over time.


What’s the Big Deal?

Presenting convenience sample data as if it were a random sample can lead to misunderstandings, especially in government decision-making, where every voice should count. When convenience samples are mistaken for a full community snapshot, decision-makers might overlook important perspectives, often from underrepresented groups. This can lead to policies that don’t fully serve everyone and erode public trust if people feel their voices were left out. Being transparent about the limits of convenience samples helps avoid these pitfalls, ensuring that decisions are made with a clear understanding of whose voices are—and aren’t—represented.


What’s Next?

In our next blog post, we’ll look at why a true random sample might not even be ideal for equitable engagement. The goal isn’t just to reach anyone; it’s to ensure we hear from everyone, especially those who are often underrepresented. Stay tuned!

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