How to Avoid Bias in Data Collection Methods

What are possible sources of bias in data collection methods?

There are several possible sources of bias in data collection methods, including:

  1. A Bias from a sampling method that only uses volunteers
  2. Undercoverage bias
  3. Nonresponse bias
  4. Response bias where responses are self-reported
  5. Response bias where the question wording is leading or confusing

The question pertains to potential sources of bias in survey data collection methods, such as volunteer sampling bias, undercoverage bias, nonresponse bias, and response bias due to self-reporting or misleading question wording.


The question addresses various potential sources of bias in the method of data collection, specifically in the context of survey research. Volunteer sampling bias occurs when the sample is made up of volunteers, potentially leading to a non-representative sample. Undercoverage bias happens when some members of the population are less likely to be included in the sample, such as those without a telephone. Nonresponse bias refers to biases that may result when certain individuals or groups are less likely to respond to a survey. Response bias from self-reported data can occur when respondents do not accurately report their true opinions or behaviors. Lastly, confusing or leading wording in a question can influence the answers received, leading again to response bias.

To avoid these biases, it is critical for researchers to carefully design their surveys and select their samples to be as representative as possible. They must also be aware of the potential influence of the survey's wording and the characteristics of the data collector on the respondents' answers.

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