title: Bayesian Inference on Predictors of Sex of the Baby.
abstract: It is well known that the sex ratio at birth is a biological constant, being about 106 boys to 100 girls. However couples have always wanted to know and decide in advance the sex of a newborn. For example, a large number of papers appeared connecting biometrical variables, such as length of follicular phase in the woman menstrual cycle or timing of intercourse acts to the sex of new baby. In this paper, we propose a Bayesian model to validate some of these theories by using an independent database. Results show that we could not show an effect of the follicular length on the sex of the baby. We also obtain a slightly larger probability, although not significant, of conceiving a female just after the mucus peak day.
authors.affiliation: Department of Statistical Sciences, University of Padua , Padua , Italy.
authors.forename: Bruno
authors.initials: B
authors.lastname: Scarpa
keywords: Bayesian hierarchical model; aggregated Bernoulli; human fertility; sex of the baby