Science Resources
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Spiegelhalter, D. (2019). The art of statistics: Learning from data. Pelican.
The best single modern book on statistical reasoning for a general reader: clear, rigorous, and honest about uncertainty, by a statistician who has spent his career on public understanding. The strongest companion to Understanding Statistics.
Sagan, C. (1995). The demon-haunted world: Science as a candle in the dark. Random House.
The definitive popular case for science as a way of thinking rather than a body of dogma, and a defence against credulity that never tips into scientism. The spirit of this whole section.
Chalmers, A. F. (2013). What is this thing called science? (4th ed.). University of Queensland Press.
The fair-minded standard introduction to what science actually is and how philosophers have argued about it. The place to start for the method itself.
The Philosophy of Science
Popper, K. (1959). The logic of scientific discovery. Hutchinson.
Falsification and the disconfirmation asymmetry at the source. Foundational; read knowing it is the starting logic, not the last word (see the Rabbit Hole).
Kuhn, T. S. (1962). The structure of scientific revolutions. University of Chicago Press.
Paradigms and how science really changes. Hugely influential and genuinely illuminating; often over-read into relativism. Read for the description, not as a charter for “all theories are equal.”
Deutsch, D. (2011). The beginning of infinity: Explanations that transform the world. Viking.
A serious physicist’s argument for good explanations as the engine of knowledge. Ambitious and contestable in places, argued in good faith. Bracing and original.
Deutsch, D. (1997). The fabric of reality. Allen Lane.
Deutsch’s earlier synthesis of quantum theory, computation, evolution, and epistemology into one worldview. Demanding; rewards the effort. His framework, clearly his own, but built with rigour.
Chamberlin, T. C. (1890). The method of multiple working hypotheses. Science, 15(366), 92–96.
A short, still-excellent classic arguing that you should hold several rival hypotheses at once rather than fall in love with one. As relevant now as when it was written.
Statistics and Evidence
Spiegelhalter, D. (2019). The art of statistics: Learning from data. Pelican.
Listed above; the rigorous core reference for reading data well.
Reinhart, A. (2015). Statistics done wrong: The woefully complete guide. No Starch Press.
A clear, slightly mischievous tour of the ways statistical analysis goes wrong, p-hacking, underpowered studies, the lot. Practical and well-aimed.
Ellenberg, J. (2014). How not to be wrong: The power of mathematical thinking. Penguin Press.
A mathematician on how quantitative reasoning sharpens everyday thinking, including survivorship bias and the misuse of statistics. Accessible and genuinely useful.
Harford, T. (2020). The data detective: Ten easy rules to make sense of statistics. Riverhead. (UK title: How to make the world add up.)
Ten clear habits for not being fooled by numbers in the wild, from a skilled economics communicator. A good companion to the Cheat Sheet.
Bracken, M. B. (2013). Risk, chance, and causation: Investigating the origins and treatment of disease. Yale University Press.
A careful, accessible treatment of how epidemiology establishes (and fails to establish) cause in medicine. Strong on confounding and the limits of observational data.
Pearl, J., & Mackenzie, D. (2018). The book of why: The new science of cause and effect. Basic Books.
The popular entry to modern causal inference: why “correlation is not causation” is not the end of the story, and how careful reasoning can get at cause. Pearl’s framing is influential and somewhat his own in emphasis; the core is sound and important.
The Psychology of Error
Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
The landmark synthesis of the two-systems view of the mind and the catalogue of cognitive biases. Essential reading, with an important caveat that is itself a teaching case: several findings it reported, notably in social priming and ego depletion, have failed to replicate, and Kahneman himself acknowledged the priming chapter had over-trusted weak studies. Read it for the framework and the core biases, hold the specific shaky results lightly, and treat the book as a live demonstration of the replication crisis it predates.
Tavris, C., & Aronson, E. (2007). Mistakes were made (but not by me): Why we justify foolish beliefs, bad decisions, and hurtful acts. Harcourt.
Why we cannot see our own motivated reasoning, including the mechanism behind the Semmelweis reflex and scientific self-deception. Reliable and sharp.
Gilovich, T. (1991). How we know what isn’t so: The fallibility of human reason in everyday life. Free Press.
How ordinary cognitive machinery manufactures and sustains false beliefs in reasonable people. Underrated, and directly relevant to the convenient-belief problem.
Dobelli, R. (2013). The art of thinking clearly. Harper.
A brisk, one-bias-per-chapter field guide to thinking errors. Useful as a quick reference; lighter and less sourced than the academic treatments above, so treat it as a prompt list rather than an authority.
Randomness, Decisions, and Forecasting
Mlodinow, L. (2008). The drunkard’s walk: How randomness rules our lives. Pantheon.
The clearest popular account of how badly humans intuit randomness and probability. Reliable and well-paced.
Gleick, J. (1987). Chaos: Making a new science. Viking.
The classic narrative introduction to chaos and non-linear dynamics, sensitive dependence, and why some systems resist prediction in principle. Still the best way in to the idea, and a bridge to systems thinking.
Taleb, N. N. (2001). Fooled by randomness: The hidden role of chance in life and in the markets. Texere.
Taleb, N. N. (2018). Skin in the game: Hidden asymmetries in daily life. Random House.
Sharp, original work on randomness, asymmetry, fat tails, and the limits of prediction, which connects directly to the manual’s hormesis and fragility threads. Tagged contested because Taleb’s combative broader claims range past his demonstrated rigour; take the core arguments on risk and asymmetry, weigh the rest on its merits.
Tetlock, P. E., & Gardner, D. (2015). Superforecasting: The art and science of prediction. Crown.
What actually distinguishes people who forecast well: probabilistic thinking, frequent updating, and intellectual humility. Evidence-based and a fine practical complement to the section’s stance on probability over certainty.
Peterson, M. (2017). An introduction to decision theory (2nd ed.). Cambridge University Press.
A proper textbook treatment of how rational choice under uncertainty is formally modelled. Technical; the reference for anyone wanting the underlying structure rather than the popularisation.
How Science Goes Wrong, and How It Self-Corrects
Ritchie, S. (2020). Science fictions: How fraud, bias, negligence, and hype undermine the search for truth. Metropolitan Books.
The best single book on the replication crisis and the structural failures of modern science, written by a researcher who is pro-science precisely in his criticism. The ideal companion to The History of Science, and a model of the anti-dogma-and-anti-scientism balance.
Goldacre, B. (2008). Bad science. Fourth Estate.
A clinician’s dismantling of health-claim nonsense, from quack remedies to misreported trials. Funny, rigorous, and a practical course in the statistics pages applied to the real world.
Goldacre, B. (2012). Bad pharma: How drug companies mislead doctors and harm patients. Fourth Estate.
The detailed case on hidden trial data, publication bias, and industry influence over medical evidence. Pairs with the “follow the money” thread in the History page.
Oreskes, N., & Conway, E. M. (2010). Merchants of doubt: How a handful of scientists obscured the truth on issues from tobacco smoke to global warming. Bloomsbury Press.
The definitive history of the manufacture of scientific doubt for commercial and political ends. Well-documented; about the politics around science, not the science itself.
Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716.
The landmark replication study itself (97 of 100 original studies significant, around 36 replications). The primary source behind the replication-crisis discussion; worth reading rather than only hearing about.
Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Medicine, 2(8), e124.
The famous, provocative argument for why a large fraction of published findings will not hold up. Influential and much-debated; read as a sharp argument that reframed the field, not as a precise literal statistic.
The History of Science
Wootton, D. (2015). The invention of science: A new history of the scientific revolution. Harper.
A rich, rigorous account of how the methods and very concept of science emerged in early modern Europe. The serious history behind the section’s History page.
Sagan, C. (1995). The demon-haunted world. Random House.
Listed above; also doubles as accessible history of the long human struggle between method and superstition.
At the Frontier
Wolfram, S. (2002). A new kind of science. Wolfram Media.
The computational-universe idea: complexity from simple iterated rules. Interesting and provocative; the grand claims (a new kind of science, a path to fundamental physics) are Wolfram’s own and not accepted by mainstream physics. A place to wander, not established ground. Fuller note on The Science Rabbit Hole.
Feynman, R. P., Leighton, R. B., & Sands, M. (1964). The Feynman lectures on physics. Addison-Wesley.
Not frontier so much as bedrock: the model of how a great scientist explains hard things with honesty about what is and isn’t known. Read for the thinking as much as the physics; freely available online.