Scientific Inference

LPS/Phil 240

Basic Information
Instructor:  Kent Johnson
Office Hours:  TTh 330-430p (and by appointment)
Office Location:  SST 755

Introduction.  In your typical bit of basic research in the sciences, some empirical data about the world are collected and processed, and at the end, sometimes a conclusion about the larger world is drawn. This is a case of scientific inference. Broadly speaking, the purpose of this course is to get a better sense of how it works, and some of the philosophical issues that lie under and alongside such practices. The readings emphasize the "citation classics" in this area -- texts and positions that philosophers of science in general should be familiar with.

Background. There is no expectation that students will already be familiar with the statistical methods that will be the topics of philosophical discussion. Instead, in weeks 1 and 4, we will survey some important elements of these methods. The purpose of these surveys will be to develop some sufficiently realistic and concrete examples, with which we can consider the philosophical positions discussed in the remaining weeks.

Requirements. Students taking the course for a grade are expected to be active participants in the seminar by taking part in the presentation and discussion of the material, and to write a term paper on a topic to be negotiated with me.

Outside Reading.

Week Topics and Readings
Extra Readings
Classical Inference: Basic examples and facts
  • Patrick Suppes 1962. "Models of data"
  • Thomas Wickens 1998. "Drawing conclusions from data: statistical methods for coping with uncertainty"
  • Prasanta Bandyopadhyay and Steve Cherry 2011. "Elementary probability and statistics: a primer"

Classical Inference: Hooray!
  • Deborah Mayo 1996. Error and the Growth of Experimental Knowledge
    •  chap 1 "Learning from error"
    • chap 13 "Toward an error-statistical philosophy of science"
  • David R. Cox 1958. "Some problems connected with statistical inference"
  • Ronald Fisher 1955. "Statistical methods and scientific induction"
  • Ronald Fisher 1962. "The place of the design of experiments in the logic of scientific inference"
  • Hasok Chang 1997. "Review of Error and the Growth of Experimental Knowledge"
Classical Inference: Boo!
  • Colin Howson and Peter Urbach 2005. Scientific Reasoning: The Bayesian Approach  (3rd ed.)
    • chap 5 "Classical inference: significance tests and estimation
    • chap 6 "Statistical inference in practice: clinical trials"
  • Jacob Cohen 1994. "The earth is round (p < .05)"

``A hypothesis that may be true may be rejected because it has not predicted observable results which have not occurred.'' — Harold Jeffreys (1961)

Bayesian Inference: Basic examples and facts
  • Amy Perfors et al 2011. "A tutorial introduction to Bayesian models of cognitive development" (at least sections 1-2)
  • Jose Bernardo 2011. "Modern Bayesian inference: foundations and objective methods"
  • Jennifer Hoeting et al 1999. "Bayesian model averaging: a tutorial"
  • Robert Kass and Adrian Rafterty 1995. "Bayes factors"
  • I. J. Good 1952. "Rational decisions"
  • Ward Edwards, Harold Lindman, and Leonard Savage 1963. "Bayesian statistical inference for psychological research"
Bayesian Inference: Hooray!
  • Colin Howson and Peter Urbach 2005. Scientific Reasoning: The Bayesian Approach (3rd ed.)
    • chap 8 "Bayesian induction: statistical theories"
    • chap 9 "Finale: some general issues"
  • Dennis Lindley 2000. "The philosophy of statistics"
  • I. J. Good 1988. "The interface between statistics and philosophy of science"
  • Michael Lee and Kenneth Pope 2006. "Model selection for the rate problem: A comparison of significance testing, Bayesian, and minimum description length statistical inference"
Bayesian Inference: Boo!
  • Deborah Mayo 1996. Error and the Growth of Experimental Knowledge
    • chap 3 "The New Experimentalism and the Bayesian Way"
    • chap 10 "Why you cannot be just a little bit Bayesian"
  • Bradley Efron 1986. "Why isn't everyone a Bayesian?"
  • Clark Glymour 1980. Theory and Evidence
    • chap 3 "Why I am not a Bayesian"
The Likelihood Principle
  • Allan Birnbaum 1962. "On the foundations of statistical inference"
  • Richard Royall 1997. Statistical Evidence: A Likelihood Approach
    • chap 1 "The first principle"
    • Appendix "The paradox of the ravens"
  • James Berger and Robert Wolpert 1988. The Likelihood Principle - Proof of Birnbaum's theorem.
  • Malcolm Forster 2006. "Counterexamples to a likelihood theory of evidence"
Model Selection
  • Malcolm Forster and Elliott Sober 1994. "How to tell when simpler, more unified, or less ad hoc theories will provide more accurate predictions"
  • Malcolm Forster 2000. "Key concepts in model selection: performance and generalizability"
  • Walter Zucchini 2000. "An introduction to model selection"
  • Elliott Sober 2004. "Likelihood, model selection, and the Quine-Duhem problem"
  • I.A. Kieseppa 1997, "Akaike information criterion, curve fitting, and the philosophical problem of simplicity"
  • I.A. Kiesesppa 2004, "AIC and large samples"
Representation, Invariance, Meaningfulness
  • Patrick Suppes 2002. Representation and Invariance of Scientific Structures
    • chap 3 "Theory of isomorphic representations"
    • chap 4 "Invariance"
  • Patrick Suppes 1951. "A set of independent axioms for extensive quantities"
  • Louis Narens 2002. "A meaningful justification for the representational theory of measurement"
  • Patrick Suppes and Joseph L. Zinnes 1963. "Basic measurement theory"
Causal Inference
  • Judea Pearl 2000. Causality: Models, Reasoning, and Inference
    • [chap 1 "Introduction to probabilities, graphs, and causal models"]
    • chap 2"A theory of inferred causation"
    • chap 3 "Causal diagrams and the identification of causal effects"
  • James Woodward 1999. "Causal Interpretation in Systems of Equations"
  • James Woodward 1997. "Explanation, Invariance, and Intervention"
  • Clark Glymour 1980. Theory and Evidence
    • chap 5 "Theory and Evidence"
  • James Bogen and James Woodward 1988. "Saving the phenomena"