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Curve Fitting, the Reliability of Inductive Inference, and the Error-Statistical Approach
10 references·8 citing·37 second hop
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this work references cited by second hop

References

  • 1936Design of Experiments4,949 cited
  • 1996Error and the Growth of Experimental Knowledge1,325 cited
  • 1977Progress and its problems towards a theory of scientific growth987 cited
  • 1967The Foundations Of Scientific Inference709 cited
  • 1994How to Tell When Simpler, More Unified, or LessAd HocTheories will Provide More Accurate Predictions660 cited
  • 2008The design of experiments380 cited
  • 1968Choice and Chance: An Introduction to Inductive Logic.320 cited
  • 1991Novel Evidence and Severe Tests152 cited
  • 2004Methodology in Practice: Statistical Misspecification Testing120 cited
  • 1997Akaike Information Criterion, Curve-fitting, and the Philosophical Problem of Simplicity113 cited

Cited by

  • 2017Evaluating Forecasts, Narratives and Policy Using a Test of Invariance73 cited
  • 2011A frequentist interpretation of probability for model-based inductive inference48 cited
  • 2010Is Frequentist Testing Vulnerable to the Base-Rate Fallacy?46 cited
  • 2022On The Philosophy of Unsupervised Learning43 cited
  • 2015Error statistical modeling and inference: Where methodology meets ontology42 cited

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  • 2022Statistical significance and its critics: practicing damaging science, or damaging scientific practice?42 cited
  • 2010The Discovery of Argon: A Case for Learning from Data?25 cited
  • 2012Philosophy of Econometrics22 cited