What is "sampling bias" and how can it affect research results?

Sampling bias refers to a systematic error that occurs when a research sample is not representative of the broader population from which it is drawn. This can lead to distorted findings because the results may inaccurately reflect the characteristics, behaviors, or opinions of the overall population. For example, if a study about a health issue only includes participants from a wealthy neighborhood, the results may not apply to individuals living in different socioeconomic circumstances, leading to conclusions that cannot be generalized.

When sampling bias is present, it undermines the validity of research because it skews the data and can lead researchers to make incorrect assumptions about the population as a whole. This is critical, as biased sampling can cause researchers to overlook important factors or misinterpret the significance of their findings. Therefore, ensuring that a sample is as representative as possible is foundational to conducting reliable and valid research.