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Convenience Sampling Bias

Also Known As: WEIRD sample bias Availability sampling bias
Aspect ID: convenience_sampling_bias

Definition

Convenience sampling bias arises when researchers sample whoever is most easily accessible rather than drawing a representative sample from the target population. The most pervasive example is psychology's over-reliance on WEIRD (Western, Educated, Industrialized, Rich, Democratic) samples, particularly American undergraduates, for conclusions claimed to be universally human.

Examples

Most foundational psychology studies on cooperation, fairness, and decision-making used US undergraduate students as subjects. When replicated with non-WEIRD populations, many results failed to hold, revealing the sample-specific nature of the original findings.

A nutritionist studies the eating habits of 'average adults' by surveying patrons at a health food café near her university. The sample is overwhelmingly health-conscious and educated, producing dietary patterns far removed from those of the general population.

A political scientist tests a new survey instrument about civic engagement by distributing it to attendees at a local town hall meeting. Since town hall attendees are already unusually politically active, the instrument appears to detect high engagement everywhere it is later deployed, masking its inability to capture apathetic or disengaged citizens.

Verification Steps
Verification Steps
Binary yes/no questions that an AI must answer to detect a reasoning pattern in a text.
Each of the 452 aspects has verification steps — simple yes/no questions designed to systematically detect whether a pattern appears in a text. For ad hominem: "Does the argument attack a person rather than their claim?" For false dichotomy: "Are only two options presented when more exist?" This ensures consistent, reproducible analysis.

Binary (yes/no) questions an LLM must answer to identify this aspect:

  1. 1

    Was the sample selected based on ease of access rather than representativeness?

    Type: binary
  2. 2

    Does the sample consist predominantly of a narrow demographic (e.g., university students, clinic patients)?

    Type: binary
  3. 3

    Are findings generalized beyond the sampled population?

    Type: binary
  4. 4

    Is the sample described as WEIRD (Western, Educated, Industrialized, Rich, Democratic)?

    Type: binary
Deep Dive
The expandable detail section on each aspect page with examples, psychology, and counter-strategies.
The Deep Dive section provides in-depth information about each aspect: a real-world example showing the pattern in action, an explanation of why it works psychologically, practical advice on how to counter it, alternative names, and links to related aspects.