Numerical Encoding of Uncertainty Phrases from 28 Human Subjects

A study of how 28 subjects numerically encoded 15 probability phrases across three sentence contexts on a 0 to 100 scale. The data was collected by Edgar M. Johnson and includes responses from 14 U.S. Army enlisted men and 14 extension college students. Analysis revealed individual consistency but significant interpersonal differences, with cluster analysis suggesting an underlying asymmetric probability scale.

Use Cases

• Modeling human interpretation of verbal probability expressions based on the numerical encoding task.
• Analyzing interpersonal differences in uncertainty perception based on the subject group comparisons.
• Developing calibrated uncertainty scales for AI systems based on the cluster analysis findings.
• Studying context effects on probability judgments based on the three-sentence context design.

Strengths

• Data is derived from a controlled study with 28 human subjects.
• Includes 15 distinct probability phrases encoded across three different sentence contexts.
• Analysis includes cluster analysis to infer underlying scale structure.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Edgar M. Johnson

Collection Method

Experimental study where subjects numerically encoded probability phrases.

Time Range

Unknown

Freshness

Last updated date is unknown.

Geography

Unknown