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Related Concept Videos

Reliability and Validity01:29

Reliability and Validity

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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Quality Control

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Related Experiment Video

Updated: Jun 22, 2026

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Prime tests and keeping proofs secret.

G Kolata

    Science (New York, N.Y.)
    |August 29, 1986
    PubMed
    Summary

    A conference on Mathematics and Computers featured diverse talks, from chaos theory to number theory. Two novel computational complexity tricks were presented, offering new insights for computer science.

    Area of Science:

    • Mathematics
    • Computer Science
    • Computational Complexity

    Background:

    • A conference convened computer scientists, mathematical physicists, and mathematicians at Stanford University.
    • The event covered a broad spectrum of topics, including chaos theory and number theory.
    • Software vendors showcased systems for problem-solving.

    Purpose of the Study:

    • To present novel findings and discussions at the intersection of mathematics and computer science.
    • To explore advancements in computational complexity.
    • To foster collaboration between researchers and industry.

    Main Methods:

    • Presentations on various mathematical and computational topics.
    • Discussions on number theory problems and chaos mathematics.

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  • Demonstrations of software systems for computational tasks.
  • Main Results:

    • Two new computer science tricks in computational complexity were unveiled.
    • Diverse mathematical and computational concepts were shared.
    • Practical applications of computational systems were explored.

    Conclusions:

    • The conference highlighted the synergy between mathematical principles and computer science advancements.
    • New computational complexity techniques offer potential for more efficient calculations.
    • Interdisciplinary collaboration is crucial for driving innovation in the field.