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Statistical Inference: The Big Picture.

Robert E Kass1

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|August 16, 2011
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Summary
This summary is machine-generated.

Statistical pragmatism offers a new framework for interpreting results beyond old debates. This inclusive philosophy emphasizes model assumptions and data connections for better statistical inference.

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Area of Science:

  • Statistics
  • Philosophy of Science

Background:

  • The field of statistics has evolved beyond historical frequentist-Bayesian debates.
  • Current statistical practices necessitate a robust framework for result interpretation.

Purpose of the Study:

  • To propose a philosophical foundation for statistical inference.
  • To introduce and define 'statistical pragmatism' as a compatible philosophy.
  • To address the mischaracterization of statistical inference in introductory courses.

Main Methods:

  • Conceptual analysis of statistical practice.
  • Development of the 'statistical pragmatism' framework.
  • Critique of traditional pedagogical approaches to statistical inference.

Main Results:

  • Statistical pragmatism provides an inclusive foundation for inference.
  • This philosophy highlights the crucial link between statistical models and observed data.
  • A proposed 'big picture' depiction offers an alternative to current introductory course models.

Conclusions:

  • Statistical pragmatism offers a unifying and practical approach to statistical inference.
  • Emphasizing assumptions and data connections enhances the interpretation of statistical results.
  • Educational reform is needed to accurately represent the process of statistical inference.