Some class-participation demonstrations for decision theory and bayesian statistics

American Statistician

Volumn 52, Issue 2, 1998, Pages 167-174

  Gelman, Andrew ^a  

^a Columbia University ^*  (United States)

Author keywords

Calibration; Expected value; Instruction; Probabilitye; Utility

Indexed keywords

EID: 0032376749     PISSN: 00031305     EISSN: 15372731     Source Type: Journal    
DOI: 10.1080/00031305.1998.10480557     Document Type: Article

References (18)

1. Alpert, M., and Raiffa, H. (1984), “A Progress Report on the Training of Probability Assessors,” in Judgment Under Uncertainty: Heuristics and Biases, eds. Kahneman, D., Slovic, P., and Tversky, A., New York: Cambridge University Press, pp. 294-305.
2. Berry, D. (1995), Statistics: A Bayesian Perspective, Belmont, CA: Duxbury Press.
3. Carlin, B., and Louis, T. (1996), Bayes and Empirical Bayes Methods for Data Analysis, London: Chapman &Hall.
4. Clayton, D., and Bemardinelli, L. (1992), “Bayesian Methods for Mapping Disease Risk,” in Geographical and Environmental Epidemiology: Methods for Small-Area Studies, eds. P. Elliott, J. Cusick, D. English, and R. Stem, Oxford: Oxford University Press, pp. 205-220.
5. Clemen, R. T. (1996), Making Hard Decisions (2nd ed.), Belmont, CA: Duxbury Press.
6. Cobb, G. (1992), ‘Teaching Statistics,” in Heeding the Call for Change: Suggestions for Curricular Action, ed. L.A. Steen, Mathematical Association of America, pp. 3-34.
7. Dorman, P. (1996), Markets and Mortality: Economics, Dangerous Work, and Value of Human Life, Cambridge University Press.
8. Gelman, A., Carlin, J. B., Stem, H. S., and Rubin, D. B. (1995), Bayesian Data Analysis, London: Chapman &Hall.
9. Gelman A., and Price, P. N. (in press), “All Maps of Parameter Estimates are Misleading,” Statistics in Medicine.
10. Gnanadesikan, M., Scheaffer, R.L., Watkins, A.E., and Witmer, J.A. (1997), “An Activity-Based Statistics Course,” Journal of Statistics Education, 5.
11. Hynes, M. E., and Vanmarcke, E. (1977), “Reliabibty of Embankment Performance Predictions,” Mechanics in Engineering, University of Waterloo Press, pp. 367-384.
12. Kahneman, D., Slovic, P., and Tversky, A. (1984), Judgment Under Uncertainty: Heuristics and Biases, New York: Cambridge University Press.
13. Kahneman, D., and Tversky, A. (1979), “Prospect Theory: An Analysis of Decision Under Risk,” Econometrica, 47, 263-291.
14. Manton, K. G., Woodbury, M. A., Stallard, E., Riggan, W. B., Creason, J. P., and Pellom, A. C. (1989), “Empirical Bayes Procedures for Stabilizing Maps of U.S. Cancer Mortality Rates,” Journal of the American Statistical Association, 84, 637-650.
15. Rhoads, S.E. (1980), Valuing Life: Public Policy Dilemmas, Boulder, CO: Westview Press.
16. Smith, J. Q. (1988), Decision Analysis: A Bayesian Approach, London: Chapman &Hall.
17. Thaler, R. H. (1992), The Winner’s Curse: Paradoxes and Anomalies of Economic Life, New York: Free Press.
18. Watson, S. R., and Buede, D. M. (1987), Decision Synthesis: the Principles and Practice of Decision Analysis, New York: Cambridge University Press.