Image: Sketchplanations
Sampling bias occurs when some members of the group you are trying to understand are less likely to be included in your data than others. Survey data is especially vulnerable to sampling bias. The data you collect is often not representative of the whole group that received the survey but rather the subgroup that was willing to complete the survey — as illlustrated in the “sketchplanation” above. So here are some quick tips to avoid this type of bias in your survey data:
Clearly define the group and related subgroups that you want to understand. Consider what might be necessary to collect sufficient data from all of the subgroups.
Follow up with those who don’t respond to the survey to understand why they didn’t respond. Did you ask the wrong questions or target the wrong audience? Apply these insights next time you are planning a survey.
Make your survey brief and easy to understand.
Finally, don’t overinterpret your survey date. Assess which types of respondents were the least likely to respond and interpret accordingly.
For a fuller explanation of types of sampling bias and strategies to avoid it, check out this SurveyMonkey article.
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