The fuzzy sets approach to poverty measurement was developed in the early 1990s and continues to be refined by scholars of economics and sociology who find the traditional "monetary-only" indicators to be inadequate and arbitrary.
This volume brings together advanced thinking on the multidimensional measurement of poverty, including the theoretical background, applications to cross-sections using contemporary European examples, and longitudinal aspects of multidimensional fuzzy poverty analysis that pay particular attention to the transitory, or impermanent, conditions that often occur during transitions to market economies.
This book will be of interest to scholars and researchers and will be a useful text on poverty for advanced students in applied statistics, urban planning, economics, and sociology.
Achille Lemmi is Professor of Economic Statistics at the University of Siena. His areas of interest and research include personal income distribution models, poverty and living conditions estimation and analysis, and poverty dynamics.
Gianni Betti is Associate Professor of Economic Statistics at the University of Siena. His areas of interest and research include poverty and living conditions analysis, equivalence scales, small area estimation and poverty mapping.
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Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called "sexy." From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.
For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.
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