1. Denise Schmandt-Besserat, “Tokens and Writing: The Cognitive Development,”SCRIPTA (2009): 145–154,

  2. “Table A-15: Alternative Measures of Labor Underutilization,” U.S. Bureau ofLabor Statistics,

  3. Jonathan Stray, “Ethics in Data Journalism: Margin of Error in Bureau of La-bor Statistics Reports,” Data Driven Journalism, 15 January 2016,

  4. George Cobb, “The Introductory Statistics Course: a Ptolemaic Curriculum,”Technology Innovations in Statistics Education, 1 (2007),

  5. James C. Scott, Seeing Like a State (New Haven: Yale University Press, 1998).

  6. David Hestenes, “Oersted Medal Lecture 2002: Reforming the Mathematical Lan-guage of Physics,” American Journal of Physics, 104 (2003),

  7. Brian Gratton and Myron P. Guttman, “Hispanics in the United States 1850–1990,” Historical Methods, 3 (2000),

  8. David Niose, “Anti-Intellectualism Is Killing America,” Psychology Today, 23 June2015,

  9. G. Kitson Clark, The Making of Victorian England (New York: Routledge, 1962),

  10. Chris Davis and Matthew Doig, “State Scraps Felon Voter List,” Sarasota Herald-Tribune, 12 July 2004,

  11. Matt Waite, “Handling Data About Race and Ethnicity,” OpenNews Source, 20June 2014,

  12. “Sixteenth Decennial Census of the United States, Instructions to Enumerators,Population and Agriculture,” U.S. Census Bureau, 1940,

  13. Jens Manuel Krogstad and Mark Hugo Lopez, “‘Mexican,’ ‘Hispanic,’ ‘Latin Amer-ican’ Top List of Race Write-ins on the 2010 Census,” Pew Research Center, 4 April2014,

  14. “Directive No. 15 as Adopted on May 12, 1977,” U.S. Census Bureau, 1977,

  15. Jerzy Wojewoda et al., “Hysteretic Effects of Dry Friction: Modelling and Ex-perimental Studies,” Philosophical Transactions of the Royal Society A, 1866 (2008),

  16. “Employment Situation Technical Note,” U.S. Bureau of Labor Statistics, 2015,

  17. Neil Irwin and Kevin Quealy, “How Not to Be Misled by the Jobs Report,” TheNew York Times, 1 May 2013, http ://

  18. “How the Government Measures Unemployment,” U.S. Bureau of Labor Statis-tics, 2015,

  19. “Employment Situation Technical Note.”

  20. Marianne Durand and Philippe Flajolet, “Loglog Counting of Large Cardinal-ities,” in ESA (2003), 605–617,

  21. Sir Arthur Conan Doyle, “The Adventure of the Blanched Soldier,” in The Case-Book of Sherlock Holmes (1927), 54.

  22. Mike Bostock et al., “One Report, Diverging Perspectives,” The New York Times,5 October 2012, http ://www.

  23. James Fallows, “Why to Get More Than 1 Newspaper, iPad Edition,” The At-lantic, 22 October 2013,

  24. Kypros Kypri et al., “Effects of Restricting Pub Closing Times on Night-timeAssaults in an Australian City,” Addiction, 2 (2011),

  25. Ibid.

  26. Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—But SomeDon’t (New York: Penguin, 2012), 484.

  27. Ibid.

  28. Sanjoy Mahajan, Street-Fighting Mathematics: The Art of Educated Guessingand Opportunistic Problem Solving (Cambridge: MIT Press, 2010).

  29. Meier and Zabell, “Benjamin Peirce and the Howland Will.”

  30. Ian Hacking, “Telepathy: Origins of Randomization in Experimental Design,” Isis, 3 (1998),

  31. Gerard E. Dalal, “Why P=0.05?”

  32. Anders Hald, “On the History of Maximum Likelihood in Relation to Inverse Probability and Least Squares,” Statistical Science, 2 (1999),

  33. Robert Kass and Adrian Raftery, “Bayes Factors,” Journal of the American Statistical Association, 430 (1995),

  34. Sharon Bertsch McGrayne, The Theory That Would Not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphantfrom Two Centuries of Controversy (New Haven: Yale University Press, 2011).

  35. Steven Raphael and Jens Ludwig, Evaluating Gun Policy: Effects on Crime and Violence (Chicago: Brookings Institution Press, 2003), 251–277,

  36. Ibid.

  37. Steven D. Levitt, “Understanding Why Crime Fell in the 1990s: Four Factors That Explain the Decline and Six That Do Not,” The Journal of Economic Perspectives, 1 (2004).

  38. Raphael and Ludwig, Evaluating Gun Policy: Effects on Crime and Violence.

  39. Kypri et al., “Effects of Restricting Pub Closing Times on Nighttime Assaultsin an Australian City.”

  40. Raphael and Ludwig, Evaluating Gun Policy: Effects on Crime and Violence.

  41. Occupational Mortality: The Registrar General’s Decennial Supplement for England and Wales, 1970–1972 (London: Her Majesty’s Stationery Office, 1978),

  42. Franz H. Messerli, “Chocolate Consumption, Cognitive Function, and Nobel Laureates,” New England Journal of Medicine (2012): 1562–1564.

  43. Greg Mankiw, “A Striking Scatterplot,” 29 March 2011,

  44. Ibid.

  45. Christian Rudder, “Exactly What to Say in a First Message,” OKCupid blog,2009,

  46. Milberger et al, “Tobacco Manufacturers’ Defence Against Plaintiffs’ Claims ofCancer Causation: Throwing Mud at the Wall and Hoping Some of It Will Stick,” Tobacco Control (December 2006): iv17–iv26,

  47. Andrew Gelman, “Statistics for Cigarette Sellers,” Chance, 3 (2012),

  48. Bikaramjit Mann and Evan Wood, “Confounding in Observational Studies Explained,” The Open Epidemiology Journal (2012),

  49. James F. Pagel, Natalie Forister, and Carol Kwiatkowki, “Adolescent Sleep Disturbance and School Performance: The Confounding Variable of Socioeconomics,” Jour-nal of Clinical Sleep Medicine, 1 (2007).

  50. Judea Pearl, Causality: Models, Reasoning, and Inference, 2nd Edition (Cambridge: Cambridge University Press, 2009).

  51. Danial Kaplan, Statistical Modeling: A Fresh Approach, Second Edition (ProjectMosaic, 2012).

  52. John Stuart Mill, A System of Logic, Vol. 1 (: 1843), 455.

  53. Matt Apuzzo and Adam Goldman, “Documents Show NY Police Watched Devout Muslims,” Associated Press, 6 September 2011,

  54. Philip Kitcher, The Advancement of Science: Science Without Legend, Objectivity Without Illusions (Oxford: Oxford University Press, 1993).

  55. Daniel Kahneman, Thinking Fast and Slow (New York: Farrar, Straus and Giroux, 2013).

  56. Jr. Richards J. Heuer, The Psychology of Intelligence Analysis (: CIA, 1999),

  57. Charles Sanders Peirce, “Some Consequences of Four Incapacities,” Journal ofSpeculative Philosophy (1868): 140–157.

  58. Tamara Munzner, “Visualization,” in Fundamentals of Computer Graphics, Third Edition, ed. Peter Shirley and Steve Marschner (AK Peters, 2009), 675–707,

  59. Justin McCarthy, “Most Americans Still See Crime Up Over Last Year,” Gallup, 21 November 2014,

  60. Ibid.

  61. Ruth Hamill, Timothy DeCamp Wilson, and Richard E. Nisbett, “Insensitivity to Sample Bias: Generalizing From Atypical Cases,” Journal of Personality and Social Psychology, 4 (1980).

  62. Ibid.

  63. Ibid.

  64. Ibid.

  65. Ibid.

  66. Angela Fagerlin, Catharine Wang, and Peter A. Ubel, “Reducing the Influence of Anecdotal Reasoning on People’s Health Care Decisions: Is a Picture Worth a Thousand Statistics?” Medical Decision Making, 4 (2005).

  67. Stray.

  68. Jessica M. Pollak and Charis E. Kubrin, “Crime in the News: How Crimes, Offenders and Victims Are Portrayed in the Media,” Journal of Criminal Justice andPopular Culture, 1 (2007).

  69. Miguel Ríos, “The Geography of Tweets,” Twitter, 31 May 2013,

  70. Moritz Stefaner, “The VIZoSPHERE, 2011,” 2011, http://www. visualizing .org/full-screen/29391.

  71. “Special Coverage of the 2014 Midterms,” FiveThirtyEight, 4 November 2014,

  72. The New York Times, “Who Will Win the Senate?” 4 November 2014,

  73. Elke Weber, “From Subjective Probabilities to Decision Weights: The Effect of Asymmetric Loss Functions on the Evaluation of Uncertain Outcomes and Events,”Psychological Bulletin, 2 (1994).

  74. Adam J. L. Harris and Adam Corner, “Communicating Environmental Risks:Clarifying the Severity Effect in Interpretations of Verbal Probability Expressions,” Journal of Experimental Psychology: Learning, Memory, and Cognition, 6 (2011).

  75. Ulrich Hoffrage et al., “Representation Facilitates Reasoning: What Natural Frequencies Are and What They Are Not,” Cognition (2002),

  76. “Visualizing Smoking Risk,” Stubborn Mule, 21 October 2010,

  77. Ibid.

  78. Phillip E. Tetlock, Expert Political Judgment: How Good Is It? How Can We Know? (Princeton: Princeton University Press, 2005).

  79. Ibid.

  80. Ibid.

  81. Paul Meehl, Clinical Versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence (Minneapolis: University of Minnesota, 1954).

  82. Quinn McNemar, “Review of Clinical Versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence by Paul E. Meehl,” The American Jour-nal of Psychology, 3 (September 1955).

  83. William M. Grove et al., “Clinical Versus Mechanical Prediction: A Meta-analysis,”Psychological Assessment, 1 (2000).

  84. Paul Meehl, “Causes and Effects of My Disturbing Little Book,” Journal of Per sonality Assessment, 3 (1986).

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