In general, we find that students tend to confuse bias in an everyday sense (unfair favoring based on opinions) with bias in a strict statistical sense (problems with samples or results based on experimental design including survey writing and sample collection). Research shows that this confusion is very frequently not resolved even after a student has completed an introductory course.

Student Notions

When presented with a prompt such as: "The researcher said that the data were biased. What does biased mean in this context?", student responses have been summarized into the following categories (in this case, categories are exclusive):

  • Statistical Notions
    • Sample is not representative; statistic calculation results in systematic differences from parameter
    • Problems with experimental design or randomness (vague)
    • Data does not represent sample (incorrect)
  • Colloquial Notions
    • Skewed; one-sided or leaning in one direction; favoring a group based on opinion
    • Manipulated; Following researcher's intent or preconception
    • Not symmetric (confusion with skew)
    • Untrue, incorrect
    • Subjective data, data based on opinions


The following HILT activities have been designed to address student misconceptions regarding "Bias" and have research that suggests they improve student learning:

Distorted Distributions