Selected works that shaped our understanding of scientific reasoning
Scientific Attitude / Scientific Method
Richard Feynman on Scientific Method.
Perlmutter, Saul, John Campbell, and Robert MacCoun. (2021). Sense & Sensibility & Science. UC Berkeley Big Ideas Course.
McIntyre, L. (2019). The Scientific Attitude: Defending Science from Denial, Fraud, and Pseudoscience. Cambridge, MA: MIT Press.
Ho, Dien. (2020). Science vs Pseudoscience. Data & Science podcast with Glen Wright Colopy.
Fooling Ourselves
Nuzzo, R. (2015). How Scientists Fool Themselves – and How They Can Stop. Humans are Remarkably Good at Self-deception. But Growing Concern about Reproducibility is Driving Many Researchers to Seek Ways to Fight their Own Worst Instincts. Nature, 526(7572), 182.
Strand, J. F. (2021). Error Tight: Exercises for Lab Groups to Prevent Research Mistakes. PsyArXiv. March 31.
Falsification and Refutation:
Popper, K. (2005). The Logic of Scientific Discovery. Taylor & Francis, New York.
On naive vs sophisticated falsification: Lakatos, I. (1980). The Methodology of Scientific Research Programmes: Volume 1: Philosophical Papers. Cambridge: Cambridge University Press.
Azoulay, P., Fons-Rosen, C., & Graff Zivin, J. S. (2019). Does Science Advance One Funeral at a Time?. American Economic Review, 109(8), 2889-2920.
Statistical Pitfalls:
Smith, G., & Cordes, J. (2019). The 9 Pitfalls of Data Science. Oxford University Press.
Smith, G., & Cordes, J. (2020). The Phantom Pattern Problem: The Mirage of Big Data. Oxford University Press.
Gelman, A., & Loken, E. (2014). The Statistical Crisis in Science. Data-dependent Analysis —a “Garden of Forking Paths”— Explains Why Many Statistically Significant Comparisons Don’t Hold Up. American Scientist, 102(6).
Abductive Reasoning:
Heckman, J. J., & Singer, B. (2017). Abducting Economics. American Economic Review, 107(5), 298-302.
Duede, E., & Evans, J. (2021). The Social Abduction of Science. arXiv preprint arXiv:2111.13251.