Statistics and Society: Measuring Inequality, Networks, and Historical Change

This session highlights novel statistical approaches to understanding inequality, social networks, and historical data. Presentations will explore alternative measures of inequality that challenge traditional metrics like the Gini coefficient, the role of probability distributions in debunking claims about the benefits of income inequality, and a federal agency's commitment to open science. Additional talks will examine the limitations of household-based social network analysis, Bayesian methods for linking historical records of enslaved individuals, and innovative statistical models for complex networks and spatially dependent data. Together, these studies push the boundaries of statistical methodology to uncover deeper insights into social and economic structures.