Думай «почему?». Причина и следствие как ключ к мышлению

Turing, A. (1950). Computing machinery and intelligence. Mind 59: 433–460.

Weisberg, D. S., and Gopnik, A. (2013). Pretense, counterfactuals, and Bayesian causal models: Why what is not real really matters. Cognitive Science 37: 1368–1381.

Глава 2. От государственных пиратов до морских свинок: становление причинного вывода

Annotated Bibliography

Galton’s explorations of heredity and correlation are described in his books (Galton, 1869, 1883, 1889) and are also documented in Stigler (2012, 2016).

For a basic introduction to the Hardy-Weinberg equilibrium, see Wikipedia (2016a). For the origin of Galileo’s quote “E pur si muove,” see Wikipedia (2016b). The story of the Paris catacombs and Pearson’s shock at correlations induced by “artificial mixtures” can be found in Stigler (2012, p. 9).

Because Wright lived such a long life, he had the rare privilege of seeing a biography (Provine, 1986) come out while he was still alive. Provine’s biography is still the best place to learn about Wright’s career, and we particularly recommend Chapter 5 on path analysis. Crow’s two biographical sketches (Crow, 1982, 1990) also provide a very useful biographical perspective. Wright (1920) is the seminal paper on path diagrams; Wright (1921) is a fuller exposition and the source for the guinea pig birth-weight example. Wright (1983) is Wright’s response to Karlin’s critique, written when he was over ninety years old.

The fate of path analysis in economics and social science is narrated in Chapter 5 of Pearl (2000) and in Bollen and Pearl (2013). Blalock (1964), Duncan (1966), and Goldberger (1972) introduced Wright’s ideas to social science with great enthusiasm, but their theoretical underpinnings were not well articulated. A decade later, when Freedman (1987) challenged path analysts to explain how interventions are modelled, the enthusiasm disappeared, and leading researchers retreated to viewing SEM as an exercise in statistical analysis. This revealing discussion among twelve scholars is documented in the same issue of the Journal of Educational Statistics as Freedman’s article.

The reluctance of economists to embrace diagrams and structural notation is described in Pearl (2015). The painful consequences for economic education are documented in Chen and Pearl (2013).

A popular exposition of the Bayesian-versus-frequentist debate is given in McGrayne (2011).

More technical discussions can be found in Efron (2013) and Lindley (1987).

References

Blalock, H., Jr. (1964). Causal Inferences in Nonexperimental Research. University of North Carolina Press, Chapel Hill, NC.

Bollen, K., and Pearl, J. (2013). Eight myths about causality and structural equation models. In Handbook of Causal Analysis for Social Research (S. Morgan, ed.). Springer, Dordrecht, Netherlands, 301–328.

Chen, B., and Pearl, J. (2013). Regression and causation: A critical examination of econometrics textbooks. Real-World Economics Review 65: 2–20.

Crow, J. F. (1982). Sewall Wright, the scientist and the man. Perspectives in Biology and Medicine 25: 279–294.

Crow, J. F. (1990). Sewall Wright’s place in twentieth-century biology. Journal of the History of Biology 23: 57–89.

Duncan, O. D. (1966). Path analysis. American Journal of Sociology 72: 1–16.

Efron, B. (2013). Bayes’ theorem in the 21st century. Science 340: 1177–1178.

Freedman, D. (1987). As others see us: A case study in path analysis (with discussion). Journal of Educational Statistics 12: 101–223. Galton, F. (1869). Hereditary Genius. Macmillan, London, UK. Galton, F. (1883). Inquiries into Human Faculty and Its Development.

Macmillan, London, UK.

Galton, F. (1889). Natural Inheritance. Macmillan, London, UK.

Goldberger, A. (1972). Structural equation models in the social sciences. Econometrica: Journal of the Econometric Society 40: 979–1001.

Lindley, D. (1987). Bayesian Statistics: A Review. CBMS-NSF Regional Conference Series in Applied Mathematics (Book 2). Society for Industrial and Applied Mathematics, Philadelphia, PA.

McGrayne, S. B. (2011). The Theory That Would Not Die. Yale University Press, New Haven, CT.

Pearl, J. (2000). Causality: Models, Reasoning, and Inference. Cambridge University Press, New York, NY.

Pearl, J. (2015). Trygve Haavelmo and 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).