Works Cited and Recommended References

Works Cited

The following sources provided the theoretical frameworks for the analysis of probability, heuristics, and statistical methodology.

• Bayes, Thomas. “An Essay towards Solving a Problem in the Doctrine of Chances.” Philosophical Transactions of the Royal Society of London, 1763. (The foundational text for Bayesian Inference).

• Bernoulli, Daniel. “Exposition of a New Theory on the Measurement of Risk.” Econometrica, vol. 22, no. 1, 1954 (originally published 1738). (Primary source for Utility Theory).

• Fisher, Ronald A. Statistical Methods for Research Workers. Oliver and Boyd, 1925. (Foundational text for Null Hypothesis Significance Testing).

• Hacking, Ian. The Emergence of Probability. Cambridge University Press, 1975. (Primary source for the Duality of Probability—objective vs. subjective).

• Huff, Darrell. How to Lie with Statistics. W. W. Norton & Company, 1954. (Primary resource for deconstructing the “Tyranny of the Average” and statistical slanting).

• Jaynes, E.T. Probability Theory: The Logic of Science. Cambridge University Press, 2003. (The primary academic defense for probability as an extension of logic).

• Kahneman, Daniel. Thinking, Fast and Slow. Farrar, Straus and Giroux, 2011. (Summarizes decades of research on the Availability Heuristic, Loss Aversion, and Prospect Theory).

• Kolmogorov, Andrey. Foundations of the Theory of Probability. 1933. (The primary source for the mathematical Axioms of Probability).

• Neyman, Jerzy, and Egon Pearson. “On the Problem of the Most Efficient Tests of Statistical Hypotheses.” Philosophical Transactions of the Royal Society of London, 1933. (Foundational source for Type I and Type II Errors).

• Tversky, Amos, and Daniel Kahneman. “Judgments Under Uncertainty: Heuristics and Biases.” Science, vol. 185, no. 4157, 1974, pp. 1124–1131. (The seminal study on the Conjunction Fallacy and the “Linda Problem”).

Recommended References

The following materials offer deeper explorations into the mathematics of chance, the philosophy of risk, and the impact of data on society.

Philosophy of Chance & Uncertainty

• Eagle, Antony. Philosophy of Probability: Contemporary Readings. Routledge, 2010. (A comprehensive anthology of modern philosophical debates on the nature of chance).

• Pascal, Blaise. Pensées. (Specifically the section on “Pascal’s Wager,” one of the first philosophical applications of Expected Value).

• Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. Random House, 2007. (Critical reading for understanding the limits of the Bell Curve and the impact of Extremistan).

Statistical Literacy & Data Ethics

• O’Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown, 2016. (Examines how statistical models can perpetuate bias if not critically examined).

• Paulos, John Allen. Innumeracy: Mathematical Illiteracy and Its Consequences. Hill and Wang, 1988. (A classic text on the social and political dangers of failing to understand basic probability).

• Rosling, Hans. Factfulness: Ten Reasons We’re Wrong About the World—and Why Things Are Better Than You Think. Flatiron Books, 2018. (A masterclass in using data to overcome the Availability Heuristic and emotional bias).

Psychology of Decision Making

• Ariely, Dan. Predictably Irrational: The Hidden Forces That Shape Our Decisions. HarperCollins, 2008. (Explores the gap between the “Rational Model” and actual human behavior).

• Gigerenzer, Gerd. Risk Savvy: How to Make Good Decisions. Viking, 2014. (Focuses on how to apply “Simple Heuristics” to make better choices in high-stakes environments like healthcare).