Thinking, Fast and Slow - Daniel Kahneman

correct answer is 41%: Applying Bayes’s rule in odds form, the prior odds are the odds for the
Blue cab from the base rate, and the likelihood ratio is the ratio of the probability of the
witness saying the cab is Blue if it is Blue, divided by the probability of the witness saying the
cab is Blue if it is Green: posterior odds = (.15/.85) × (.80/.20) = .706. The odds are the ratio of
the probability that the cab is Blue, divided by the probability that the cab is Green. To obtain
the probability that the cab is Blue, we compute: Probability (Blue) = .706/1. 706 = .41. The
probability that the cab is Blue is 41%.
not too far from the Bayesian: Amos Tversky and Daniel Kahneman, “Causal Schemas in
Judgments Under Uncertainty,” in Progress in Social Psychology, ed. Morris Fishbein
(Hillsdale, NJ: Erlbaum, 1980), 49–72.
University of Michigan: Richard E. Nisbett and Eugene Borgida, “Attribution and the
Psychology of Prediction,” Journal of Personality and Social Psychology 32 (1975): 932–43.
relieved of responsibility: John M. Darley and Bibb Latane, “Bystander Intervention in
Emergencies: Diffusion of Responsibility,” Journal of Personality and Social Psychology 8
(1968): 377–83.
17: Regression to the Mean
help of the most brilliant statisticians: Michael Bulmer, Francis Galton: Pioneer of Heredity
and Biometry (Baltimore: Johns Hopkins University Press, 2003).
standard scores: Researchers transform each original score into a standard score by subtracting
the mean and dividing the result by the standard deviation. Standard scores have a mean of
zero and a standard deviation of 1, can be compared across variables (especially when the
statistica {he deviatiol distributions of the original scores are similar), and have many desirable
mathematical properties, which Galton had to work out to understand the nature of correlation
and regression.
correlation between parent and child: This will not be true in an environment in which some
children are malnourished. Differences in nutrition will become important, the proportion of
shared factors will diminish, and with it the correlation between the height of parents and the
height of children (unless the parents of malnourished children were also stunted by hunger in
childhood).
height and weight: The correlation was computed for a very large sample of the population of
the United States (the Gallup-Healthways Well-Being Index).
income and education: The correlation appears impressive, but I was surprised to learn many
years ago from the sociologist Christopher Jencks that if everyone had the same education, the