Sampling bias

Definition

Sampling bias occurs when certain members of a population are systematically more likely to be selected in a sample than others. This results in a sample that is not representative of the population.

5 Must Know Facts For Your Next Test

1. Sampling bias can lead to inaccurate conclusions about the population.
2. Common causes include non-random sampling methods, self-selection, and exclusion of certain groups.
3. It undermines the validity of statistical inference drawn from the sample.
4. Detection of sampling bias often requires comparing sample characteristics with known population characteristics.
5. Mitigating sampling bias involves using random sampling techniques and ensuring all subgroups are adequately represented.

Review Questions

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

Related terms

Random Sampling:

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

Non-response Bias: Bias that occurs when individuals chosen for the sample do not respond, leading to underrepresentation.

Stratified Sampling:

A technique where the population is divided into subgroups (strata) and random samples are taken from each stratum.