Title:
Quantifying Gerrymandering using Markov Chain Monte Carlo Algorithms
Quantifying Gerrymandering using Markov Chain Monte Carlo Algorithms
| dc.contributor.advisor | Vigoda, Eric | |
| dc.contributor.author | Wahal, Samarth | |
| dc.contributor.committeeMember | Vempala, Santosh | |
| dc.contributor.department | Computer Science | |
| dc.contributor.department | Computer Science | |
| dc.date.accessioned | 2020-11-09T16:59:15Z | |
| dc.date.available | 2020-11-09T16:59:15Z | |
| dc.date.created | 2019-12 | |
| dc.date.issued | 2019-12 | |
| dc.date.submitted | December 2019 | |
| dc.date.updated | 2020-11-09T16:59:15Z | |
| dc.description.abstract | We look at the rules and regulations surrounding redistricting in the United State. We examine Markov Chain Monte Carlo algorithms that are able to sample redistricting plans adhering to these rules. We implement the algorithm proposed by Fifield et al. [11] and use it to sample plans for the state of Georgia. We count the number of Republican House seats won for each sampled plan. We compare Georgia’s existing redistricting plan to this distribution in order to test the null hypothesis that Georgia is not gerrymandered. Our results show that we fail to reject this null hypothesis. | |
| dc.description.degree | Undergraduate | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1853/63854 | |
| dc.language.iso | en_US | |
| dc.publisher | Georgia Institute of Technology | |
| dc.subject | Markov Chain | |
| dc.subject | Markov Chain Monte Carlo | |
| dc.subject | MCMC | |
| dc.title | Quantifying Gerrymandering using Markov Chain Monte Carlo Algorithms | |
| dc.type | Text | |
| dc.type.genre | Undergraduate Thesis | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | College of Computing | |
| local.contributor.corporatename | School of Computer Science | |
| local.contributor.corporatename | Undergraduate Research Opportunities Program | |
| local.relation.ispartofseries | Undergraduate Research Option Theses | |
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| thesis.degree.level | Undergraduate |