Human Decision Data Demonstrating Quantum Zeno Effect

This dataset provides empirical evidence for a quantum Zeno effect in human decision-making processes. It was created by James M. Yearsley and published in 2020 to support the application of quantum principles in decision theory.

Use Cases

• Analyze patterns of opinion change under continuous judgment conditions to test quantum collapse postulates.
• Model decision-making processes using quantum theory frameworks based on experimental evidence.
• Investigate the relationship between judgment frequency and the slowing or freezing of opinion change.

Strengths

• Data is associated with a published study demonstrating a novel quantum Zeno effect in human cognition.
• Dataset is openly licensed under CC0-1.0, allowing for unrestricted reuse.

Limitations

• Specific data structure, including row count, column names, and file formats, is not provided in the input.
• The experimental scope and sample size of the underlying human study are unknown.

Provenance

Source

dryad

Collection Method

Experimental data from a study on quantum effects in human decision making.

Freshness

Data was last updated on 2020-06-24.