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  • Author: Czesław Domański x
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Can economic stress affect secondary sex ratio in Poland?

The ratio of male to female births described as the male proportion is expected to be about 1.06. The secondary sex ratio can be influenced by various stresses experienced by parents (e.g., parents' exposure to chemical and physical pollution, natural phenomena, wars and economic crises). The seminal study in this field speculated that fewer goods and services than needed or desired might sufficiently stress human populations to lower the secondary sex ratio. The main purpose of this study is to examine the relationship between economic stress and the fluctuations of sex ratio at birth in Poland. The statistical analysis was based on annual demographic data obtained from year-books issued by the Central Statistical Office on the overall number of male and female live births in Poland in the years 1956-2005 as well as on the annual data of percentage change in total private consumption. In order to verify the hypothesis that the observed time-series of the secondary sex ratio in Poland declines with deterioration in economic conditions, we constructed mathematical models (ARIMA) of both analyzed phenomena following the statistical procedure proposed by Catalano and Bruckner [2005]. We found a statistically significant decline of SSR in Poland over the last 50 years. The decrease appeared to be stronger in villages than in towns. However, the consumption rate as related to the strength of economic stress had no effect on the fluctuation of the sex ratio at birth.

Abstract

In the presence of massive data coming with high heterogeneity we need to change our statistical thinking and statistical education in order to adapt both - classical statistics and software developments that address new challenges. Significant developments include open data, big data, data visualisation, and they are changing the nature of the evidence that is available, the ways in which it is presented and the skills needed for its interpretation. The amount of information is not the most important issue – the real challenge is the combination of the amount and the complexity of data. Moreover, a need arises to know how uncertain situations should be dealt with and what decisions should be taken when information is insufficient (which can also be observed for large datasets). In the paper we discuss the idea of computational statistics as a new approach to statistical teaching and we try to answer a question: how we can best prepare the next generation of statisticians.