Survey biases can occur in any survey, but they are more likely to occur when the survey is conducted by humans. Humans are biased by their own opinions and experiences, which may lead them to give an answer that fits with those opinions and experiences. 

Survey biases can occur in any type of survey. In this article, we will discuss how often survey bias can occur in research and its implications.


How often Do Survey Biases Occur

So, how often do survey biases occur? It’s hard to say exactly how often people are biased when they take surveys because there isn’t a lot of research on the subject. 

But there are some things we can learn from what we do know. One thing researchers have found is that if you give people a choice between two options, they’re more likely to pick one over the other. 

This means that if you’re asking your respondents about their views on a certain issue and you offer them two sides. If one is more popular than the other, they’ll be more likely to choose the one that’s less popular.

This may not be true in some cases because people are still going to pick their favorite option sometimes, but this could make it seem like there’s bias in your results. However, if you’re careful with your wording and design your survey so that it’s clear which side people should be voting for.

Furthermore, the most common survey bias occurs when people who are more familiar with certain topics or concepts tend to give a different answer from those who are unfamiliar with the topic. For example, if you ask an engineer how much money they make, they may give a higher number than someone who is not an engineer. 

This is known as “social desirability” and it occurs because people often want to please those in authority or who are conducting the survey.


Types of Survey Biases

Surveys are a great way to collect data and make a point, but they’re not always perfect. When you’re running a survey, there are several ways your results might be biased. 

Here are the most common ones:

  1. Research Bias: Research bias occurs when the researcher is influenced to find a particular result in their research. This can happen if the researcher has preconceived ideas about what they think will happen, or if they are being paid by a certain side. For example, a researcher might subconsciously choose a question that reflects their own opinion on an issue, or they may have been given funding by one group and choose questions that reflect that group’s opinions. Or, if the researcher is biased against a certain group of people, such as women or immigrants, the data may be skewed in their favor. This type of bias happens because the researcher has an agenda and wants to prove something which means they might have trouble being objective.
  2. Recall Bias: A bias where people are more likely to remember positive experiences than negative ones, even though they had fewer negative experiences overall. The effect of recall bias is that it causes us to remember things differently than they actually occurred, which can lead to incorrect conclusions. For example, if someone is asked about their favorite color and answers “blue,” this may be considered a biased response because it could indicate that if you asked them about their favorite color again after some time had passed, they might say red instead.
  3. Reporting Bias: This refers to the tendency for people who are asked to participate in surveys to give answers based on their own opinions rather than what is true or accurate because of the way the questions are worded or phrased (e.g., “I agree with X”). If you want your survey results to be accurate, you should make sure your questions are as clear and unbiased as possible by using specific terms that make it easy for respondents to answer honestly without feeling pressured into saying something they don’t really mean. The effect of reporting bias is that it causes people to lie more often on subsequent surveys because they know they will not be punished for lying, but they also won’t be rewarded for telling the truth either. 
  4. Observation Bias: Observation bias occurs when people are asked about their own behavior in a survey rather than about other people’s behavior. This type of bias causes people to view themselves as more honest than others do and therefore more likely to report honestly on surveys than they would if they were asked questions about other people’s behavior instead of their own.
  5. Selection Bias: This happens when only certain people are chosen for participation in a survey and those people will give biased responses due to their own opinions, beliefs, and experiences that were left out of their answers because there was no space for them on the questionnaire or because it was not possible for them to answer all questions correctly as they might have misunderstood some parts of them (e.g. if you ask someone if they like chocolate bars they might say “yes” even though they don’t like chocolate bars at all).


Effects of Each Type of Survey Biases

  • Research Bias: Having research bias in a study can lead to biased results because it skews the data in favor of the researcher’s own opinion. This can result in distorted results and invalid conclusions, which can be dangerous when used in medical research. For example, a study that found a drug was effective at curing cancer may have been biased by the researchers’ desire for the drug to be approved for use in treating cancer patients.
  • Observation Bias: Observation bias can lead to skewed results if researchers miss important details about how people behave in different situations or what they think about a particular topic. This might result from such factors as limited resources or an inability to fully understand the phenomenon being observed. If a researcher were observing a phenomenon for which they had no prior experience, this could lead to an incorrect interpretation of the phenomenon being observed due to a lack of familiarity with how it should appear or behave for it to meet their expectations.
  • Recall Bias: This is one of the most common types of bias that occurs when surveying people who have already experienced something. If you ask someone about their experience with a product or service, and they tell you it wasn’t great because they got a defective model, then this is going to skew your results. You need to be sure that each person has actually used the product before being interviewed so that it doesn’t skew your results in this way.
  • Selection Bias: This can lead to the results of a survey being skewed due to the sample being too small or unrepresentative of the target population. For example, if we only had a certain type of person come to our survey and ask them all the same questions, we would have biased results that would not be representative of our target audience. Or, if you’re studying the effects of exercise on weight loss, you might choose participants who are already exercising. This could lead to your results being skewed by the fact that the group you chose was already in better shape than usual.
  • Reporting Bias: This occurs when researchers are unconsciously or consciously biased towards reporting certain types of information rather than others, which can lead them to report findings in a way that supports their own beliefs or biases rather than objectively evaluating data from research participants’ responses.

How To Correct Each Type Of Survey Bias

The first step to correcting any kind of biased survey is to understand the type of bias that’s present and how it affects your results. There are five main types of biases, with each one having its own effect on your data: recall bias, reporting bias, observation bias, selection bias, and research bias.

  • Research Bias: The best way to prevent research bias is to use a random sampling method, such as a simple random sample or stratified random sample. This ensures that every participant in the study will be included, regardless of how they might have answered a previous question. If you’re using a stratified random sample, you’ll want to ensure that all participants are from similar demographics (age, gender/gender identity/sexual orientation, etc.). For example, if you’re studying young adults with an interest in health services research and you want to ensure that all participants are under 25 years of age, then you should stratify by age group. You can then use your results to validate those findings among younger participants only. You can also use open-ended questions instead of multiple-choice questions so that respondents feel more comfortable sharing their opinions freely without having them filtered by predefined categories like “strongly agree” or “disagree.”
  • Reporting Bias: To guard against this possibility, try running several surveys with different questions so you get different responses from each one but know that this solution is imperfect because some people may still lie intentionally even after attempting multiple distinct surveys.
  • Recall Bias: To correct for recall bias, you can ask your respondents to rate their experience on a scale from 1 to 10, rather than just ranking the level of their satisfaction or dissatisfaction with a product or service. You can also give each participant a number of points that correspond with the number of times he or she uses the product or service at a rate of 2 per month. That way, participants will be able to identify with the scores they receive because they will see how well they stack up against others’ experiences.
  • Observation Bias: If you’re conducting a survey and your participants are biased in their answers, you’ll be able to see that in their responses. For example, if someone is less likely to admit that they have a problem with the product, then their answers will reflect this. You can adjust for this by asking questions about how many people have had the same experience as the respondent and what methods they used in order to try to fix the problem.
  • Selection Bias: To correct this, ask questions that tap into both sides of an issue and make sure you collect data from everyone who takes part in your survey regardless of how they voted on something.



In conclusion, the bias in surveys is a problem that has been around for decades and is still present today. The best way to avoid these biases is to pay attention to how your survey was constructed, as well as its purpose and the criteria it used to gather data. 

Also, if you find yourself relying on a particular question wording and it is still giving biased results, you may need to adjust your question wording or eliminate it altogether.


  • Olayemi Jemimah Aransiola
  • on 9 min read


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