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Clever girls come more often

Statistics and the female orgasm

Munich, 04/06/2010

Women are not more likely to achieve an orgasm when their partners are well off. This is one of the take-home lessons from an analysis conducted by LMU researchers Professor Torsten Hothorn and Esther Herberich. The result clearly refutes the conclusion reached by a study that made headlines last year. Statistical analysis of the responses of more than 1500 Chinese women to a questionnaire on health and family life had led British and Dutch investigators to conclude that women were more likely to have orgasms when their male partners happened to be high earners. When Hothorn and Herberich re-evaluated the original data for teaching purposes, they discovered that the reported effect was actually an artefact caused by an error in the statistical software used to analyse the data. “Our analysis showed that the women's educational level in particular, but also general health and age, were associated with reported frequencies of orgasms” says Herberich. The LMU researchers have now published their results in a paper written together with the authors of the original study. “The primary study was actually based on data that are freely available”, remarks Hothorn. “Its ease of accessibility greatly enhances the scientific value of the original survey, because it allows statistical inferences to be independently checked by other interested groups, and either be confirmed or − as in this case − refuted”. (Evolution and Human Behavior online, March 2010)

The finding made headlines worldwide: Chinese women experience orgasm more often with wealthy partners. Thomas V. Pollet from the University of Groningen in the Netherlands and Daniel Nettle from Newcastle University in the UK came to this conclusion based on an analysis of data obtained from 1534 Chinese women, who had participated in the Chinese Health and Family Life Survey (CHFLS) and provided detailed information on their personal lives. The researchers not only inferred that their result was also applicable to women in Western societies, they also proposed a biological explanation for their controversial claim. In many models of evolution, the achievement of orgasm by the female is taken to be an indicator of the evolutionary fitness of the male partner − and a large income would be expected to make the male more attractive and desirable.

Hothorn and Herberich reanalysed the Chinese dataset for for teaching purposes, but they were unable to replicate the result originally reported. They eventually discovered that the original conclusion could be attributed to an error in the statistical software used by Pollet and Nettle. “It turned out that the authors had considered a whole range of possible statistical models with which to analyse their data, and had finally chosen an incorrect model as the best-fitting one” says Herberich, who re-examined the data as part of her Diploma thesis. “When we applied the  appropriate statistical technique to the data, we got a very different picture. It emerged that the frequency of orgasm was most highly associated with the educational level of the women, and was also influenced by their general health and age. Younger and healthier women were more likely to achieve sexual climax than older and less healthy women. The income level of the partner turned out to be  insignificant in this context.”

The LMU researchers have now published the results of their new analysis together with the authors of the original paper. “This rapid correction was possible only because the data on which the previous study was based are publicly accessible”, says Hothorn. “Otherwise we would not have been able to test the initial conclusions. It should therefore become general scientific practice not just to publish the results of the statistical analysis, but also make the original data and details of the analytical procedures available to other researchers. In this way, anyone with the necessary expertise can check how robust the published conclusions really are.“ (CA/suwe)


„A re-evaluation of the statistical model in Pollet and Nettle 2009”;
Esther Herberich, Torsten Hothorn, Daniel Nettle, Thomas V. Pollet;
Evolution and Human Behavior, Band  31, S. 150–151, März 2010;

Diplom-Statistikerin Esther Herberich
LMU Munich Department of Statistics
Tel.: +49- (0)89-2180-3198
Mobil: +49- (0)163-6805944

Prof. Dr. Torsten Hothorn
LMU Munich Department of Statistics
Tel.: +49- (0)89-2180-6407

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