Research Topics:

Data Analysis | Quantitative Research

Content Type:

Glossary

Bias Definition

A systematic tendency of a sample to misrepresent the population. Biases may be caused by improper representation of the population in the sample, interviewing techniques, wording of questions, data entry, etc.

In marketing research, bias refers to any factor that skews data collection, analysis or interpretation. In other words, bias is the presence of errors that deviate from the true population. Bias can occur throughout a study, whether it happens in a missed step in the research process or incorrect results collection. There typically are several types of bias in research: sampling bias, nonresponse bias, response bias, question bias, question-order bias and information bias. Bias can lead to inaccurate insights or conclusions. Properly conducted research occurs when researchers work to reduce or eliminate bias. 

Why should I care about bias?

It is valuable for consumers and businesses to know that no research study is completely free of bias. That said, most researchers work to reduce bias so their findings can be considered as accurate and as complete as possible. Accurate results can lead to better outcomes and more effective business strategies for business and industry.

While no one purposely adds bias to research studies – it undermines the credibility of findings – unintentional biases can affect anyone involved in the study design process. Any bias in research can lead to data that is misleading or outright false. But as diligent as researchers work to create bias-free study, there is no study that is completely free of bias.