Further Reading: Why Statistics Matters

For Enjoyment and Inspiration

Wheelan, C. (2013). Naked Statistics: Stripping the Dread from the Data. W. W. Norton. The most accessible and entertaining introduction to statistical thinking available. Wheelan writes like a journalist (which he is) and makes every concept relatable. If you read one book alongside this course, make it this one.

Rosling, H., Rosling, O., & Rosling Rönnlund, A. (2018). Factfulness: Ten Reasons We're Wrong About the World — and Why Things Are Better Than You Think. Flatiron Books. The late Hans Rosling's masterwork on using data to see the world clearly. Not a statistics textbook, but a powerful argument for data literacy. See Case Study 2 in this chapter.

Ellenberg, J. (2014). How Not to Be Wrong: The Power of Mathematical Thinking. Penguin. A mathematician's argument that quantitative reasoning is common sense pushed to its logical limits. Covers many statistical concepts with wit and clarity.

For Context on Statistics and Society

O'Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown. A mathematician's examination of how statistical models and algorithms can perpetuate bias and harm. Essential reading for the AI and ethics themes in this course.

Criado Perez, C. (2019). Invisible Women: Data Bias in a World Designed for Men. Abrams Press. How the failure to include women in data collection leads to a world that doesn't work for half the population. A powerful example of the theme "who's missing from the data."

For Reference

Triola, M. F. (2021). Elementary Statistics (14th ed.). Pearson. The most widely adopted introductory statistics textbook. More formal and comprehensive than this book. Good for additional examples and practice problems.

Moore, D. S., McCabe, G. P., & Craig, B. A. (2021). Introduction to the Practice of Statistics (10th ed.). W. H. Freeman. Another excellent standard textbook, known for its emphasis on data production and analysis.

Online Resources

Gapminder (gapminder.org) Hans Rosling's foundation. Interactive tools for exploring global data. The "Dollar Street" feature is particularly powerful for understanding how people live across income levels worldwide.

Our World in Data (ourworldindata.org) Research and data visualizations on the world's largest problems. Excellent for finding real datasets and understanding global trends. Run by researchers at the University of Oxford.

Seeing Theory (seeing-theory.brown.edu) A beautiful interactive website that visualizes statistical concepts. Created by Brown University students. Especially useful for probability and distribution concepts (Chapters 8-10).

Khan Academy: Statistics and Probability (khanacademy.org) Free video lessons covering every topic in this course. Good for supplemental explanations when a concept isn't clicking.

Articles and Papers

Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251). The landmark study discussed in Case Study 1. Attempted to replicate 100 published psychology studies and found that only 36% produced significant results the second time.

Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453. The study referenced in Section 1.4 about healthcare algorithm bias against Black patients. Technical but readable, and a powerful illustration of how statistical assumptions have real consequences.

Podcasts

Cautionary Tales with Tim Harford Stories about the human side of data and decision-making. Each episode is a standalone narrative that illustrates statistical concepts through historical events and mistakes.

More or Less (BBC) A weekly podcast dedicated to examining the statistics behind news stories. Excellent for developing the habit of asking "is that number right?"

Note: All recommendations use the citation honesty system. Tier 1 (verified) sources have full citations. The descriptions represent genuine, well-known resources.