RESEARCH COLLOQUIUM ON COMPUTATIONAL SOCIAL SCIENCE/DATA SCIENCES – Robert Axtell – Working with Heavy-Tailed Data: A Tutorial

When:
November 1, 2019 @ 3:00 pm – 4:00 pm
2019-11-01T15:00:00-04:00
2019-11-01T16:00:00-04:00
Where:
CENTER FOR SOCIAL COMPLEXITY SUITE, 3RD FLOOR, RESEARCH HALL
Cost:
Free
Contact:
Karen Underwood
7039939298

Research Colloquium on Computational Social Science/Data Science

Robert Axtell
Professor Computational Social Science PhD Program
Department of Computational and Data Sciences
George Mason University

Working with Heavy-Tailed Data: A Tutorial

Friday, November 01, 3:00 p.m.
Center for Social Complexity Suite, 3rd Floor Research Hall

All are welcome to attend.

Abstract:
This will be a hands-on talk in which I will illustrate challenges and pitfalls of manipulating and statistically describing data which are extremely skew and possibly large in quantity. Motivated mainly by models from economics (e.g., firms and cities) and finance, datasets with millions of observations, both continuous and discrete, will be analyzed and plotted, with and without binning. There will be some discussion of parameter estimation but this will not be the primary focus of the talk. Heavy-tailed size distributions, the corresponding weighted-distributions, and the related ideas of moment distributions and size-biased sampling will all be discussed. Terminology such as ‘scaling’ and ‘scale-free’ will be unpacked and illustrated. The relation of Zipf-style rank-size plots to probability distributions will be developed. The competition between power law and lognormal distributions to represent heavy-tailed data will be addressed, including the ability of the lognormal to mimic a power law. Finite size effects and truncated distributions will also be discussed.