Sampling bias

Definition

Sampling bias occurs when a sample is not representative of the population from which it was drawn, leading to skewed or invalid results. It can arise from improper sampling techniques or systematic exclusions.

5 Must Know Facts For Your Next Test

1. Sampling bias can lead to inaccurate conclusions about a population.
2. Common causes include non-random sampling methods and undercoverage of certain groups.
3. It affects the external validity of research findings.
4. Methods such as stratified sampling can help mitigate sampling bias.
5. Identifying and addressing sampling bias is crucial for reliable statistical analysis.

Review Questions

• What is sampling bias and how does it affect statistical analysis?
• Name two common causes of sampling bias.
• How can researchers minimize the impact of sampling bias in their studies?

Related terms

Random Sampling:

A method where each member of a population has an equal chance of being selected in the sample.

Stratified Sampling:

A technique where the population is divided into strata, and random samples are taken from each stratum to ensure representation.

External Validity: The extent to which research findings can be generalized to other settings or populations.