Walter Mebane

Professor, Political Science, LSA Center for Political Studies Statistics, LSA

Statistical analysis of election results

My primary project, election forensics, concerns using statistical analysis to try to determine whether election results are accurate.  Election forensics methods use data about voters and votes that are as highly disaggregated as possible.  Typically this means polling station (precinct) data, sometimes ballot box data.  Data can comprises hundreds of thousands or millions of observations.  Geographic information is used, with geographic structure being relevant.  Estimation involves complex statistical models.  Frontiers include:  distinguishing frauds from effects of strategic behavior;  estimating frauds probabilities for individual observations (e.g., polling stations);  adjoining nonvoting data such as from in-person election observations.

COntact

(607) 592-0546

wmebane@umich.edu

Website

Location

Ann Arbor

Methodologies

Machine Learning / Statistics

Applications