In our previous tip, we discussed how question randomization works and how it helps minimize selection bias in surveys. How do you find out if your data is biased? A systematic error is the key; you'll notice a pattern your answers have been following. You might also see your respondents showing a tendency to agree to whatever you are asking. You can avoid this by not asking leading questions.

Selection bias or selection effect can distort your survey data and leave you with a sample that doesn't represent the audience you were planning to analyze.

Let's learn how answer randomization can help in minimizing selection bias.

The answer randomization approach allows you to re-arrange answer choices so your respondents won't select a choice purely out of memory. Applying this to all question types can give you a more accurate survey. You can randomize, flip, or rotate choices for each respondent or sort the choices in ascending order each time. Unlike question randomization, you can choose to avoid a few options from being randomized too.

Do you need help in minimizing response bias? We'll be back with yet another tip soon.