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Abstract Details
Activity Number:
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630
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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IMS
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Abstract - #303125 |
Title:
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Risk-Limiting Election Audits Using Stratified Random Samples
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Author(s):
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Michael Higgins*+ and Philip Stark and Ronald Rivest
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Companies:
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University of California at Berkeley and University of California at Berkeley and Massachusetts Institute of Technology
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Address:
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, , ,
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Keywords:
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Auditing ;
Elections ;
Stratified random sample ;
0-1 knapsack
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Abstract:
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Votes in elections are often tallied using machines. The machine counts may differ from what a hand count would show. Risk-limiting audits test the null hypothesis that machine-count outcome differs from the hand-count outcome, regardless of the cause of the difference. For contests that span multiple counties, existing election audit laws--which do not call for risk-limiting audits--typically require each county in the contest to hand count the ballots in a set of precincts selected at random from that county. This is a stratified random sample of precincts; the strata are counties. We show that, for risk-limiting audits using stratified random samples, a conservative P-value can be obtained by solving a 0-1 knapsack problem.
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