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The Computational Social Science Workshop (MACSS) and the Workshop on Quantitative Research Methods in Education, Health, and Social Sciences (QMEHSS) Present
The Computational Social Science Workshop at the University of Chicago cordially invites you to attend this week's talk:
Summary: Our classical statistical arsenal for extracting truth from data often fails to produce correct predictions. Uncertainty, blurry evidence and multiple possible solutions may trip up even the best interrogator. Info-metrics – the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information – provides a consistent and efficient framework for constructing models and theories with minimal assumptions. It reveals the simplest solution, model or story, that is hidden in the observed information. My talk will be based on my new book ‘Foundations of Info-Metrics: Modeling, Inference, and Imperfect Information,’ http://info-metrics.org/ in which I develop and examine the theoretical underpinning of info-metrics and provide extensive interdisciplinary applications. In this talk I will discuss the basic ideas via a small number of graphical representations of the model and theory and will then present a number of interdisciplinary real-world examples of using that framework for modeling and inference.
A light lunch will be provided by Cedar's.
Amos Golan is a Professor in the Department of Economics and Director of the Info-Metrics Institute at American University. His main area of research is information, information processing and optimal decision rules based on efficient use of information (Info-Metrics). Golan is an External Professor at the Santa Fe Institute, as well as a Senior Associate at Pembroke College in Oxford.
Suggested background:
- Attached in Repository: Info‐Metrics for Modeling and Inference.
- Attached in Repository: Interval estimation: An information theoretic approach.
The 2018-2019 Computational Social Science Workshop meets Thursdays from 11 a.m. to 12:20 p.m. in Kent 120. All interested faculty and graduate students are welcome.
Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the issues page of the workshop's public repository on GitHub. Further instructions are documented in the Computational Social Science Workshop's README on Github.