Socioeconomic deprivation as measured by the index of multiple deprivation and its association with low sex hormone binding globulin in women

ACKNOWLEDGEMENTS M.L., I.L. and A.H.H. participated in the study concept and design, acquisition of data, study analysis, interpretation of data, drafting of the manuscript. D.M. provided statistical expertise. R.D., A.J.H., and A.F. participated in the interpretation of data and critical revision of the manuscript.Peer reviewedPublisher PD

Hypothesis Testing Interpretations and Renyi Differential Privacy

Differential privacy is a de facto standard in data privacy, with applications in the public and private sectors. A way to explain differential privacy, which is particularly appealing to statistician and social scientists is by means of its statistical hypothesis testing interpretation. Informally, one cannot effectively test whether a specific individual has contributed her data by observing the output of a private mechanism---any test cannot have both high significance and high power. In this paper, we identify some conditions under which a privacy definition given in terms of a statistical divergence satisfies a similar interpretation. These conditions are useful to analyze the distinguishability power of divergences and we use them to study the hypothesis testing interpretation of some relaxations of differential privacy based on Renyi divergence. This analysis also results in an improved conversion rule between these definitions and differential privacy

Neuronal Correlation Parameter in the Idea of Thermodynamic Entropy of an N-Body Gravitationally Bounded System

Understanding how the brain encodes information and performs computation requires statistical and functional analysis. Given the complexity of the human brain, simple methods that facilitate the interpretation of statistical correlations among different brain regions can be very useful. In this report we introduce a numerical correlation measure that may serve the interpretation of correlational neuronal data, and may assist in the evaluation of different brain states. The description of the dynamical brain system, through a global numerical measure may indicate the presence of an action principle which may facilitate a application of physics principles in the study of the human brain and cognition

The Effect of Fixed and Random Models in the Interpretation of Biological Data

Problem statement: Data on variation of sugar content in maize Ogi, fermented maize flour, obtained from 4 maize hybrids subjected to 5 different days of fermentation were used to test the effects of fixed and random statistical models on the interpretation of biological results. Approach: The data were subjected to analysis of variance using both fixed and random models. Results: Highly significant difference (p = 0.1) was present among hybrids, days of fermentation and interaction of hybrids and days, where the fixed model was used. On the other hand, where the random model was assumed, the interaction component of variance was found not to be significantly different from zero contrary to the findings with the fixed model. Conclusion/Recommendations: The results indicate that the statistical model used may influence interpretation of biological results

Labor market data

A guide to the use and interpretation of labor market data (employment, unemployment, and wages). Important statistical sources are surveyed and their histories outlined.Labor market

Ambiguous model learning made unambiguous with 1/f priors

What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the answer depends on the prior expectations of the dynamics of the model parameter that is to be inferred from the data. Local time constraints on the priors are insufficient to pick one interpretation over another. On the other hand, nonlocal time constraints, induced by a $1/f$ noise spectrum of the priors, is shown to permit learning of a specific model parameter even when there are infinitely many equally plausible interpretations of the data. This transition is inferred by a remarkable mapping of the model estimation problem to a dissipative physical system, allowing the use of powerful statistical mechanical methods to uncover the transition from indeterminate to determinate model learning.Comment: 8 pages, 2 figure

The Falsification of Nuclear Forces

We review our work on the statistical uncertainty analysis of the NN force. This is based on the Granada-2013 database where a statistically meaningful partial wave analysis comprising a total of 6713 np and pp published scattering data from 1950 till 2013 below pion production threshold has been made. We stress the necessary conditions required for a correct and self-consistent statistical interpretation of the discrepancies between theory and experiment which enable a subsequent statistical error propagation and correlation analysisComment: 4 pages. Conference Proceedings. 21st International Conference on Few-Body Problems in Physics (FB21