As you sample, be careful not to introduce sampling error into your research through practices like convenience sampling.
Sampling error happens when the sample does not represent the larger population.
Convenience sampling happens when the researcher only samples the portion of a population that is easily accessible to them.
Watch this video from Elon University Poll to learn more about the errors that can come from sampling, and how to design your sample so as to reduce them.
For Example…
If you are a student at Middlebury College, and only sampled Middlebury students for a survey about the experiences of college students nationwide during the COVID-19 pandemic, that would be a convenience sample. While it is perfectly acceptable to make a survey which only targets Middlebury College students, you cannot ensure that the views of these students accurately reflect those of college students across the country. As such, you must limit the scope of your question to this one specific college, rather than claim the survey to be more broadly representative.
What’s the right amount of people to include in a sample? The general rule of thumb is that the larger the sample, the better, as a more extensive sample, in theory, brings you closer to encapsulating the entire population you’re trying to study. However, the more we grow our sample size, the more expensive, time-consuming and complicated the research endeavor becomes. Thus, there is no perfect number for a good sample, especially if you select your sample carefully and thoroughly.
While there is no perfect number, you can use one of these sample size calculators to figure out the appropriate sample size for your research (here are calculators from AI-Therapy Statistics, ClinCalc.com, Creative Research Systems, and Raosoft).
Personal Project
You want to reduce error and bias as much as you can with your sample. To do so, use a sample size calculator to identify a target sample size, try to collect the largest sample that your project can reasonably afford, and make sure that your sampling strategy is well designed. Start thinking through how you will reach more people with your survey. In addition, make sure that you are not introducing bias through convenience sampling. In the next sections, you will learn about different sampling methods.
