the emergence of causal calculus. Econometric Theory 31: 152–179. Special issue on Haavelmo centennial.

Provine, W. B. (1986). Sewall Wright and Evolutionary Biology. University of Chicago Press, Chicago, IL.

Stigler, S. M. (2012). Studies in the history of probability and statistics, L: Karl Pearson and the rule of three. Biometrika 99: 1–14.

Stigler, S. M. (2016). The Seven Pillars of Statistical Wisdom. Harvard University Press, Cambridge, MA.

Wikipedia. (2016a). Hardy-Weinberg principle. Available at: https://en.wikipedia.org/wiki/Hardy-Weinberg-principle (last edited: Oc- tober 2, 2016).

Wikipedia. (2016b). Galileo Galilei. Available at: https://en.wikipedia.org/wiki/Galileo_Galilei (last edited: October 6, 2017).

Wright, S. (1920). The relative importance of heredity and environment in determining the piebald pattern of guinea-pigs. Proceedings of the National Academy of Sciences of the United States of America 6: 320–332.

Wright, S. (1921). Correlation and causation. Journal of Agricultural Research 20: 557–585.

Wright, S. (1983). On “Path analysis in genetic epidemiology: A critique.” American Journal of Human Genetics 35: 757–768.

Глава 3. От доказательств к причинам. Преподобный Байес знакомится с мистером Холмсом

Annotated Bibliography

Elementary introductions to Bayes’s rule and Bayesian thinking can be found in Lindley (2014) and Pearl, Glymour, and Jewell (2016).

Debates with competing representations of uncertainty are presented in Pearl (1988); see also the extensive list of references given there.

Our mammogram data are based primarily on information from the Breast Cancer Surveillance Consortium (BCSC, 2009) and US Preventive Services Task Force (USPSTF, 2016) and are presented for instructional purposes only.

“Bayesian networks” received their name in 1985 (Pearl, 1985) and were first presented as a model of self-activated memory. Applications to expert systems followed the development of belief updating algorithms for loopy networks (Pearl, 1986; Lauritzen and Spiegelhalter, 1988).

The concept of d-separation, which connects path blocking in a diagram to dependencies in the data, has its roots in the theory of graphoids (Pearl and Paz, 1985). The theory unveils the common properties of graphs (hence the name) and probabilities and explains why these two seemingly alien mathematical objects can support one another in so many ways. See also “Graphoid,” Wikipedia.

The amusing example of the bag on the airline flight can be found in Conrady and Jouffe (2015, Chapter 4).

The Malaysia Airlines Flight 17 disaster was well covered in the media; see Clark and Kramer (October 14, 2015) for an update on the investigation a year after the incident. Wiegerinck, Burgers, and Kappen (2013) describes how Bonaparte works. Further details on the identification of Flight 17 victims, including the pedigree shown in Figure 3.7, came from personal correspondence from W. Burgers to D. Mackenzie (August 24, 2016) and from a phone interview with W. Burgers and B. Kappen by D. Mackenzie (August 23, 2016).

The complex and fascinating story of turbo and low-density parity-check codes has not been told in a truly layman-friendly form, but good starting points are Costello and Forney (2007) and Hardesty (2010a, 2010b). The crucial realization that turbo codes work by the belief propagation algorithm stems from McEliece, David, and Cheng (1998). Efficient codes continue to be a battleground for wireless communications; Carlton (2016) takes a look at the current contenders for “5G” phones (due out in the 2020s).

References

Breast Cancer Surveillance Consortium (BCSC). (2009). Performance measures for 1,838,372 screening mammography examinations from 2004 to 2008 by age. Available at: http://www.bcsc-research.org/statistics/performance/screening/2009/perf_age.html (accessed October 12, 2016).

Carlton, A. (2016). Surprise! Polar codes are coming in from the cold. Computerworld. Available at: https://www.computerworld.com/article/3151866/mobile-wireless/surprise-polar-codes-are-coming-in-from-the-cold.html (posted December 22, 2016).

Clark, N., and Kramer, A. (October 14, 2015). Malaysia Airlines Flight 17 most likely hit by Russian-made missile, inquiry says. New York Times.

Conrady, S., and Jouffe, L. (2015). Bayesian Networks and Bayesia Lab: A Practical Introduction for Researchers. Bayesia USA, Franklin, TN.

Costello, D. J., and Forney, G. D., Jr. (2007). Channel coding: The road to channel capacity. Proceedings of IEEE 95: 1150–1177. Hardesty, L. (2010a). Explained: Gallager codes. MIT News. Available at: http://news.mit.edu/2010/gallager-codes-0121 (posted: January 21, 2010).

Hardesty, L. (2010b). Explained: The Shannon limit. MIT News. Available at: http://news.mit.edu/2010/explained-shannon-0115 (posted January 19, 2010).

Lauritzen, S., and Spiegelhalter, D. (1988). Local computations with probabilities on graphical structures and their application to expert systems (with discussion). Journal of the Royal Statistical Society, Series B 50: 157–224.

Lindley, D. V. (2014). Understanding Uncertainty. Rev. ed. John Wiley and Sons, Hoboken, NJ.

McEliece, R. J., David, J. M., and Cheng, J. (1998). Turbo decoding as an instance of Pearl’s “belief propagation” algorithm. IEEE Journal on Selected Areas in Communications 16: 140–152.

Pearl, J. (1985). Bayesian networks: A model of self-activated memory for evidential reasoning. In Proceedings, Cognitive Science Society (CSS-7). UCLA Computer Science Department, Irvine, CA.

Pearl, J. (1986). Fusion, propagation, and structuring in belief networks. Artificial Intelligence 29: 241–288.

Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann, San Mateo, CA.

Pearl, J., Glymour, M., and Jewell, N. (2016). Causal Inference in Statistics: A Primer. Wiley, New York, NY.

Pearl, J., and Paz, A. (1985). GRAPHOIDS: A graph-based logic for reasoning about relevance relations. Tech. Rep. 850038 (R-53-L). Computer Science Department, University of California, Los Angeles. Short version in B. DuBoulay, D. Hogg, and L. Steels (Eds.) Advances in Artificial Intelligence — II, Amsterdam, North Holland, 357–363, 1987.

US Preventive Services Task Force (USPSTF) (2016). Final recommendation statement: Breast cancer: Screening. Available at: https://www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/breast-cancer-screening1 (updated: January 2016).

Wikipedia. (2018). Graphoid. Available at: https://en.wikipedia.org/wiki/Graphoid (last edited: January 8, 2018).

Wiegerinck, W., Burgers, W., and Kappen, B. (2013). Bayesian networks, introduction and practical applications. In Handbook on Neural Information Processing (M. Bianchini, M. Maggini, and L. C. Jain, eds.). Intelligent Systems Reference Library (Book 49). Springer, Berlin, Germany, 401–431.

Глава 4. Осложнители и наоборот: как убить прячущуюся переменную

Annotated Bibliography

The story of Daniel has frequently been cited as the first controlled trial; see, for example, Lilienfeld (1982) or Stigler (2016). The results of the Honolulu walking study were reported in Hakim (1998).

Fisher Box’s lengthy quote about “the skillful interrogation of Nature” comes from her excellent biography of her father (Box,