# Sandbox

## Vampirical

The following quotation can be found here in an article by Gelman and Weakliem entitled, "Of beauty, sex and power: Statistical challenges in estimating small effects":

This ability of the theory to explain findings in any direction is also pointed out by Freese (2007), who describes this sort of argument as "more 'vampirical' than 'empirical'--unable to be killed by mere evidence."

Gelman and Weakliem are criticizing research which putatively detects an effect merely because statistical significance is obtained on either side of zero or, in the case of ratio of females to males, 50%. In particular, they contest the results of studies which claim that “beautiful parents have more daughters, violent men have more sons and other sex-related patterns.” They also analyze so-called Type M (magnitude) errors and Type S (sign) errors.

This is a Type M (magnitude) error: the study is constructed in such a way that any statistically-significant finding will almost certainly be a huge overestimate of the true effect. In addition there will be Type S (sign) errors, in which the estimate will be in the opposite direction as the true effect.

Discussion

1. As a long-term research project, determine via literature and art how the notion of “beautiful” has changed through the ages and across cultures.

2. The imbalance between baby daughters and baby sons produced by beautiful people somehow went from the original article’s (not statistically significant) 4.7% to 8% when dealing with the largest comparison (the most beautiful parents on a scale of 1 to 5) to 26% and finally to 36% via a typo in the New York Times.

3. The authors, based on their analysis, say “There is no compelling evidence that “Beautiful parents produce more daughters.” Nevertheless, why did the original paper have so much appeal?

4. As a check, the authors used People magazine’s “list of the fifty most beautiful people” from 1995 to 2000 to find the offsprings. There were “157 girls out of 329 children, or 47.7% girls (with a standard error 2.8%).” Instead of more females, fewer were produced.

5. The authors note “the structure of scientific publication and media attention seem to have a biasing effect on social science research.” Explain what they mean by a “biasing effect.”